Description:SYSTEM AND METHOD TO CONTROL POWER FLOW OF BATTERYPACK(S)
TECHNICAL FIELD
Generally, the present disclosure relates to a system and method for battery management systems. Particularly, the present disclosure relates to the system and method for controlling power flow of a battery pack.
BACKGROUND
Battery packs, particularly those used in electric vehicles, energy storage systems, and portable electronics, are composed of multiple cell arrays that require careful management to ensure safe and efficient operation. During charging and discharging, various factors such as cell temperature and voltage levels significantly impact battery performance, longevity, and safety.
Conventionally, the power flow control systems operate with a fixed C-rate, which is computed during the manufacturing of the cells or the battery pack. Consequently, the charging rate or discharging rate of the battery pack is fixed, and therefore, the power flow is constant from the source end to the load end. Furthermore, thermal management is achieved by comparing a temperature value to a predefined threshold and subsequently maintaining an optimal temperature. Further, in another technique, a voltage value is compared to a fixed, predefined threshold voltage value, and therefore, an optimal power flow is maintained in the battery system.
However, there are certain problems associated with the existing or above-mentioned mechanism of controlling the power flow of a battery pack. For instance, the fixed C-rate suffers from a lack of adaptability and responsiveness to real-time operating conditions. Further, by relying on fixed C-rates and a fixed predefined threshold value for temperature and voltage, the system is not able to account for dynamic factors such as ambient temperature changes, aging of battery cells, or varying load demands. Consequently, the rigidity led to suboptimal charging or discharging, increased thermal stress, and accelerated cell degradation. Moreover, using static thresholds may either overly restrict performance or fail to react quickly enough to prevent hazardous conditions, thereby compromising both efficiency and safety in modern battery applications.
Therefore, there exists a need for a mechanism for controlling the power flow of a battery pack that is efficient, accurate, and overcomes one or more problems as mentioned above.
SUMMARY
An object of the present disclosure is to provide a system of smartly controlling the charging and discharging rate of a battery pack and subsequently enhancing the battery life.
Another object of the present disclosure is to provide a method for smartly controlling the charging and discharging rate of a battery pack and subsequently enhancing the battery life.
In accordance with an aspect of the present disclosure, there is provided a system for controlling power flow of at least one battery pack, the system comprises:
- at least one temperature sensor connected to at least one cell array of the at least one battery pack;
- at least one voltage sensor connected to the at least one cell array of the at least one battery pack; and
- a microcontroller communicably coupled with the at least one temperature sensor and the at least one voltage sensor,
wherein the microcontroller is configured to control charging and discharging rate of the at least one battery pack based on inputs received from the at least one temperature sensor and the at least one voltage sensor.
The system for controlling power flow of at least one battery pack, as described in the present disclosure, is advantageous in terms of enhancing battery safety and efficiency by enabling real-time control of charging and discharging based on temperature and voltage data. Specifically, by continuously monitoring the temperature and voltage data through dedicated sensors, the system prevents hazardous conditions such as overcharging, overheating, or thermal runaway. Consequently, the energy input and output are optimized in real time, thereby enhancing charging efficiency and energy utilization during discharge.
In accordance with another aspect of the present disclosure, there is provided a method for controlling power flow of at least one battery pack, the method comprises, the method comprises:
- receiving voltage values corresponding to the at least one cell array to a microcontroller;
- comparing a first C-rate limit, a second C-rate limit, and a third C-rate limit, via a microcontroller;
- computing a minimum C-rate limit based on the comparison, via the microcontroller;
- generating a first instruction signal and a second instruction signal based on the computed minimum C-rate limit, via the microcontroller; and
- sending the first instruction signal to a charging source and the second instruction signal to the load power controller, via the microcontroller.
Additional aspects, advantages, features, and objects of the present disclosure would be made apparent from the drawings and the detailed description of the illustrative embodiments constructed in conjunction with the appended claims that follow.
It will be appreciated that features of the present disclosure are susceptible to being combined in various combinations without departing from the scope of the present disclosure as defined by the appended claims.
BRIEF DESCRIPTION OF DRAWINGS
The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the appended drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the present disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale. Wherever possible, like elements have been indicated by identical numbers.
Embodiments of the present disclosure will now be described, by way of example only, with reference to the following diagrams wherein:
Figure 1 illustrates a block diagram of a system to control power flow of a battery pack, in accordance with an embodiment of the present disclosure.
Figure 2 illustrates a flow chart for controlling power flow of a battery pack, in accordance with another embodiment of the present disclosure.
In the accompanying drawings, an underlined number is employed to represent an item over which the underlined number is positioned or an item to which the underlined number is adjacent. A non-underlined number relates to an item identified by a line linking the non-underlined number to the item. When a number is non-underlined and accompanied by an associated arrow, the non-underlined number is used to identify a general item at which the arrow is pointing.
DETAILED DESCRIPTION
The following detailed description illustrates embodiments of the present disclosure and ways in which they can be implemented. Although some modes of carrying out the present disclosure have been disclosed, those skilled in the art would recognize that other embodiments for carrying out or practicing the present disclosure are also possible.
As used herein, the terms “battery pack”,
“battery packs”, and “at least one battery pack” are used interchangeably and refer to a collection of individual battery cells, or combination of battery cells, or cell array(s) that are arranged and connected to provide the required voltage, capacity, and energy output to power the bike's motor and other electrical components. The battery pack consists of multiple cells linked in series and/or parallel, ensuring vehicle power to operate over the desired range. The battery pack is designed to handle high currents during acceleration, regenerative braking, and high-speed riding while maintaining an optimal balance between performance, weight, and safety. Further, the battery pack also incorporates components such as a battery management system, thermal management system, and protective casing. The battery management system monitors the health of each cell within the pack, ensuring that voltage and temperature levels stay within safe limits, preventing overcharging, deep discharge, and thermal runaway. The thermal management systems, such as, but not limited to, cooling plates or vents, dissipate heat generated during charging and discharging, ensuring that the cells remain within optimal temperature ranges for maximum performance and longevity. Additionally, the protective casing safeguards the cells from physical damage and environmental factors such as moisture or dust, ensuring the pack remains durable and safe for long-term use in demanding conditions.
As used herein, the terms “temperature sensor”, “temperature sensors” and “plurality of temperature sensors” are used interchangeably and refer to a component that monitors the temperature of various parts of the system, such as the battery cells, voltage sensing module, current sensing module, and processing unit. The temperature sensors are critical for ensuring the system operates within safe temperature ranges, as extreme temperatures affect the performance and safety of the battery pack. Further, by detecting temperature variations, the temperature sensors provide real-time data to the processing unit, enabling the sensors to make informed decisions regarding cooling or heating mechanisms to maintain optimal battery performance and prevent thermal runaway or damage.
As used herein, the term “cell array”, “cells” and “array” are used interchangeably and refer to a structured arrangement of individual battery cells, configured in series and/or parallel to form a battery pack. Each cell in the array is a single electrochemical unit capable of storing and releasing electrical energy. The cells are the building blocks of the battery system, and the configuration determines the overall voltage, capacity, and energy density of the pack. The cell array is designed to optimize the performance of the EV, ensuring that the battery pack provides sufficient energy for the vehicle's operation while maintaining safety and efficiency. The microcontroller monitors and manages the individual cells within the array to ensure uniform performance and prevent overcharging, deep discharging, or overheating.
As used herein, the term “voltage sensor”, “voltage sensors” and “plurality of voltage sensors” are used interchangeably and refer to an electronic device used to measure and monitor the voltage levels within an electrical system, such as a battery pack in an electric vehicle (EV). The voltage sensor helps in controlling the power flow by providing real-time voltage data to the Battery Management System (BMS) or a microcontroller, which then adjusts and optimizes performance and ensures safety. The voltage sensors detect fluctuations in battery voltage and help prevent overcharging, deep discharging, and voltage imbalances among cells. By integrating with the microcontroller, the voltage sensors enable efficient power management, helping regulate the charging and discharging process to enhance battery longevity and prevent failures. The two main types of voltage sensors are direct voltage sensors and indirect voltage sensors. The direct voltage sensors measure voltage by connecting directly to the power source, used in low-voltage applications like battery packs. The indirect voltage sensors, such as capacitive and resistive voltage dividers, use electromagnetic or resistive properties to determine voltage without direct contact. Further, the method of operation depends on the sensor type; the resistive dividers reduce voltage proportionally for safe measurement, and capacitive sensors detect voltage variations without affecting circuit performance. Subsequently, the sensors send signals to the BMS or power control unit, which processes the data and adjusts power flow, accordingly, ensuring stable and efficient battery operation.
As used herein, the terms “microcontroller”, “controller”, and “embedded controller” are used interchangeably and refer to an integrated circuit designed to govern specific operations in embedded systems. The microcontroller typically includes a processor core, memory (both RAM and flash), and programmable input/output peripherals on a single chip. The microcontroller is used to execute control functions in a variety of applications, ranging from consumer electronics to industrial automation. Specifically, the microcontroller implements algorithms for voltage regulation, such as PID (Proportional-Integral-Derivative) control, to maintain the output voltage within specified limits. Further, the microcontroller monitors key parameters such as input voltage, output voltage, and output current, thus ensuring safe and efficient operation.
As used herein, the terms “state of charge”, “battery charge level”, “charge percentage” and “SoC” are used interchangeably and refer to a parameter that represents the remaining energy in a battery as a percentage of the total capacity. The SoC is used to control the power flow of a battery pack by determining the amount of charge left and regulating charging or discharging accordingly. In an electric vehicle (EV), the Battery Management System (BMS) or a microcontroller continuously monitors the SoC to prevent overcharging, deep discharging, and inefficient energy use. An optimised SoC ensures optimal battery performance, prolongs lifespan, and maintains vehicle efficiency. By using SoC data, the system adjusts power output, limits charging rates, and optimizes regenerative braking to enhance energy utilization. The types of SoC estimation methods include coulomb counting, open-circuit voltage (OCV) measurement, and model-based estimation. The coulomb counting calculates SoC by integrating the charge or discharge current over time. The OCV measurement determines SoC based on the battery’s voltage when at rest, providing accurate results and requiring long stabilization times. Further, the model-based estimation, such as Kalman filtering or neural networks, combines multiple data points (current, voltage, temperature) for high-accuracy predictions. The method of SoC-based power control involves real-time adjustments, as when SoC is low, charging rates are increased, or power output is limited. Therefore, the dynamic adjustments ensure efficient power flow and battery protection.
As used herein, the term “no-load voltage”, “open circuit voltage” and “static voltage” are used interchangeably and refer to the voltage of a battery when the battery is not supplying or receiving current. The no-load voltage serves as an important parameter for estimating the state of charge (SoC) and monitoring battery health. Further, as the no-load voltage directly correlates with the chemical state of the battery, the no-load voltage helps to control power flow by determining the optimal charging or discharging strategy. In an electric vehicle (EV) battery pack, the Battery Management System (BMS) or a microcontroller uses no-load voltage to assess battery conditions and prevent overcharging or deep discharging, thereby enhancing battery longevity and efficiency. The no-load voltage estimation methods include direct measurement, look-up table mapping, and model-based estimation. The direct measurement involves reading the battery’s voltage after a rest period with no current flow, providing high accuracy. The look-up table mapping compares the measured voltage with a pre-defined dataset to estimate the SoC. The model-based estimation integrates factors such as temperature, internal resistance, and load history to improve accuracy. The method of controlling power flow using no-load voltage involves adjusting charging and discharging rates based on the no-load voltage value. Therefore, the dynamic voltage-based control ensures safe and efficient battery operation.
As used herein, the term “lookup table”, “reference table”, “mapping table” and “index table” are used interchangeably and refer to a pre-defined data structure used by the microcontroller to map sensor inputs, such as temperature, voltage, or SoC to predefined actions or system responses. The table contains a set of values that correspond to specific sensor readings and associated threshold levels that define critical points of operation. For example, the table maps a certain temperature value or SoC value to a safety protocol, such as activating battery restraints, shutting down power systems, or triggering alerts. The lookup table allows the microcontroller to quickly compare real-time sensor data with pre-calculated responses, enabling swift action based on predefined safety criteria. The table's entries are based on extensive testing, modelling, or empirical data, allowing the system to react appropriately under different scenarios. The advantage of this approach is that it allows for more accurate, efficient, and context-specific control, improving vehicle safety and minimizing the risk of damage or injury during battery-related incidents.
As used herein, the term “C-rate” refers to a measure of the rate at which a battery is charged or discharged relative to the maximum capacity. The C-rate is defined as a ratio of the applied current to the battery’s nominal capacity. Numerically, a 1C rate denotes that the battery is charged or discharged at a current equal to the full capacity in one hour, and a 0.5C rate takes two hours, and a 2C rate takes only 30 minutes. The C-rate plays a crucial role in controlling power flow in a battery pack, as a higher C-rates lead to increased heat generation and potential degradation, whereas a lower C-rates improve battery lifespan and efficiency. The Battery Management System (BMS) continuously monitors the C-rate to ensure safe operation by adjusting power flow accordingly. The different types of C-rate control include constant C-rate charging, variable C-rate charging, and derating-based C-rate control. The constant C-rate charging applies a fixed charge or discharge current, ensuring a predictable charging profile. The variable C-rate charging dynamically adjusts the charge rate based on factors such as temperature and state of charge (SoC) to optimize performance. The derating-based C-rate control reduces the allowable C-rate under specific conditions, such as high temperatures, excessive voltage differentials, or low SoC, to prevent battery degradation. The method of controlling power flow using C-rate involves continuously monitoring real-time conditions (such as SoC, temperature, and voltage balance) and adjusting the charging or discharging current to ensure safe and efficient operation.
As used herein, the term “delta cell voltage” and “differential cell voltage” are used interchangeably and refer to a difference in voltage between the highest and lowest individual cells within a battery pack. The delta cell voltage is a key parameter for assessing cell balancing, battery health, and operational safety. A large delta voltage value indicates an imbalance, suggesting that some cells are overcharged, and the rest of the cells are undercharged, leading to inefficiencies and potential degradation. The microcontroller monitors the delta cell voltage in real time to determine the necessity of corrective actions, such as active or passive cell balancing. The controlling power flow based on delta cell voltage helps prevent overcharging, deep discharging, and thermal runaway, ensuring that the pack operates efficiently and safely. The different types of delta cell voltage management methods include passive balancing, active balancing, and voltage-based derating. The passive balancing dissipates excess charge from higher-voltage cells as heat to equalize voltages. The active balancing redistributes charge from higher-voltage cells to lower-voltage ones, improving efficiency and prolonging battery life. The voltage-based derating involves reducing the charging or discharging rate when the delta cell voltage exceeds a certain threshold, preventing excessive stress on weaker cells. The method for controlling power flow involves continuous monitoring of individual cell voltages through the BMS or the microcontroller, which then determines whether balancing is required, or a decreased C-rate is required to prevent further imbalances.
As used herein, the term “threshold delta cell voltage”, “voltage offset limit”, and “delta voltage limit” are used interchangeably and refer to a predefined limit for the difference in voltage between the highest and lowest individual cells in a battery pack. The threshold acts as a safety and performance parameter to determine the required corrective actions are needed to maintain battery health and efficiency. The exceedance of the delta cell voltage with respect to the threshold indicates an imbalance that leads to overcharging, deep discharging, increased internal resistance, and thermal issues. Further, to ensure stable operation, the microcontroller continuously monitors the voltage difference and implements control strategies, such as derating the charge/discharge current or activating cell balancing mechanisms. Subsequently, by enforcing a threshold, the microcontroller helps prevent excessive voltage deviations that degrade battery lifespan and performance. The types of threshold delta cell voltage control strategies include fixed threshold, dynamic threshold, and adaptive threshold. The fixed threshold uses a predetermined voltage limit beyond which corrective actions are taken. The dynamic threshold varies depending on factors such as temperature, state of charge (SoC), and battery age, allowing more flexibility in different operating conditions. The adaptive threshold relies on machine learning or historical battery data to continuously adjust limits based on real-time performance trends. The method for controlling power flow involves continuous monitoring of individual cell voltages by the BMS, which compares the delta cell voltage against the set threshold. If the threshold is exceeded, the BMS may reduce charging current, limit discharge power, initiate active/passive balancing, or trigger safety warnings. This ensures the battery operates within optimal conditions, preventing further imbalance and extending its overall lifespan.
As used herein, the term “delta cell temperature” and “differential cell temperature” are used interchangeably and refer to a difference in temperature between the hottest and coldest individual cells within a battery pack. The delta cell temperature variation occurs due to differences in internal resistance, charging/discharging rates, cooling efficiency, or manufacturing inconsistencies. The excessive delta cell temperature leads to thermal runaway, uneven aging, and reduced efficiency. The microcontroller monitors delta cell temperature in real-time to detect abnormalities and take corrective actions, such as adjusting power flow, activating cooling systems, or triggering safety measures. Therefore, maintaining a low delta cell temperature ensures uniform cell performance and extends battery lifespan.
As used herein, the term “threshold delta temperature”, “temperature offset limit”, and “delta temperature limit” are used interchangeably and refer to a predefined limit for the difference in temperature between the hottest and coldest cells in a battery pack. The threshold delta temperature is set to prevent excessive thermal imbalances, which lead to uneven aging, performance degradation, and potential safety hazards such as thermal runaway. Further, as the delta temperature exceeds the threshold, the microcontroller takes corrective action to maintain battery pack stability. The threshold value depends on factors such as battery chemistry, operating conditions, and cooling system efficiency. Properly managing threshold delta temperature ensures uniform energy distribution, enhances efficiency, and extends battery life. The three primary types of threshold delta temperature management are fixed threshold, adaptive threshold, and predictive threshold. The fixed threshold sets a constant maximum allowable delta temperature, typically between 3°C and 10°C, depending on the battery type. The adaptive threshold adjusts dynamically based on factors such as, but not limited to, State of Charge (SoC), load conditions, and ambient temperature, allowing for greater flexibility in power management. The predictive threshold utilizes historical data, thermal modeling, and machine learning algorithms to anticipate and mitigate temperature imbalances before they reach critical levels. The method for controlling power flow involves continuous monitoring of cell temperatures by the microcontroller, comparing the delta temperature against the set threshold. As the threshold is exceeded, the microcontroller reduces charging/discharging current, activates cooling systems, or redistributes power within the pack to balance the temperature.
As used herein, the term “first instruction signal” refers to a control signal generated by the microcontroller or safety system in response to sensor data and the minimum C-rate limit. The signal serves as an initial trigger to control the charging rate of the battery pack. For instance, in case the system detects that the battery has experienced overcharging or is under a force that exceeds safe limits, the first instruction signal prompts the activation of restraint systems to control the charging rate. The first instruction signal is crucial for enabling real-time response to potentially hazardous situations. The first instruction signal is typically generated based on comparisons of computed C-rates, allowing the microcontroller to detect dangerous conditions rapidly.
As used herein, the term “second instruction signal” refers to a control signal generated by the microcontroller or safety system in response to sensor data and the minimum C-rate limit. The signal serves as an initial trigger to control the discharging rate of the battery pack. For instance, in case the system detects that the battery has experienced overcharging or is under a force that exceeds safe limits, the second instruction signal prompts the activation of restraint systems, to control the discharging rate at the load end. The second instruction signal is crucial for enabling real-time response to potentially hazardous situations. The second instruction signal is typically generated based on comparisons of computed C-rates, allowing the microcontroller to detect dangerous conditions rapidly.
As used herein, the term “charging source”, “power source” and “source” refer to a device that supplies electrical energy to recharge a battery pack. In electric vehicles (EVs) and energy storage systems, the charging source controls the power flow by regulating voltage, current, and charging duration to ensure safe and efficient battery operation. The charging source varies in power levels and charging strategies, depending on battery chemistry and application. The key role of a charging source is to prevent overcharging, optimize charging speed, and maintain battery health by adjusting charging parameters dynamically. Advanced charging sources integrate with Battery Management Systems (BMS) to monitor real-time battery conditions and adjust power delivery accordingly. The types of charging sources include Constant Voltage (CV), Constant Current (CC), and hybrid CC-CV chargers. The constant voltage chargers maintain a fixed voltage while allowing current to decrease as the battery reaches full charge, preventing overvoltage damage. The constant current chargers supply a steady current until the battery reaches a preset voltage, ensuring uniform energy distribution. The CC-CV method, commonly used in lithium-ion batteries, starts with constant current charging and then switches to constant voltage mode when the battery approaches full charge. The method of controlling power flow involves the charging source adjusting output voltage and current based on feedback from the BMS, temperature sensors, and SoC estimation algorithms.
As used herein, the term “load power controller”, “load current controller” and “load management unit” refer to a device that regulates and manages the power flow from a battery pack to connected loads, ensuring efficient energy distribution while protecting the battery from over-discharge or excessive current draw. In electric vehicles (EVs) and energy storage systems, the load power controller monitors real-time parameters such as battery voltage, current, state of charge (SoC), and temperature to adjust power delivery dynamically. The primary function is to optimize energy usage, prevent battery strain, and extend battery lifespan by controlling the output based on demand and battery health. The load power controllers often integrate with a Battery Management System (BMS) and communicate with other vehicle or system controllers to regulate power flow efficiently. The types of load power controllers include linear regulators, switching regulators (DC-DC converters), and smart power controllers. The linear regulators provide a stable output voltage and dissipate excess energy as heat. The switching regulators, such as buck, boost, and buck-boost converters, use high-frequency switching to efficiently step up or step down voltage and minimize energy loss. The smart power controllers utilize microcontrollers, AI algorithms, and real-time feedback loops to dynamically adjust power flow based on battery conditions and load requirements. The method of controlling power flow involves sensing the battery voltage, current, and thermal state, then adjusting power output by modulating duty cycles, switching frequencies, or voltage levels.
In accordance with an aspect of the present disclosure, there is provided a system for controlling power flow of at least one battery pack, the system comprises:
- at least one temperature sensor connected to at least one cell array of the at least one battery pack;
- at least one voltage sensor connected to the at least one cell array of the at least one battery pack; and
- a microcontroller communicably coupled with the at least one temperature sensor and the at least one voltage sensor,
wherein the microcontroller is configured to control charging or discharging rate of the at least one battery pack based on inputs received from the at least one temperature sensor and the at least one voltage sensor.

Referring to figure 1, in accordance with an embodiment, there is described a system 100 for controlling power flow of a battery pack 102. The system 100 comprises at least one temperature sensor 104 connected to at least one cell array 106 of the battery pack 102, at least one voltage sensor 108 connected to the at least one cell array 106 of the battery pack 102, and a microcontroller 110 communicably coupled with the at least one temperature sensor 104 and the at least one voltage sensor 108. Further, the microcontroller 110 is configured to control charging or discharging rate of the battery pack 102 based on inputs received from the at least one temperature sensor 104 and the at least one voltage sensor 108. Furthermore, the microcontroller 110 is configured to send a first instruction signal to a charging source 112 and a second instruction signal to a load power controller 114.
The system for controlling the power flow of a battery pack 102 operates by integrating at least one temperature sensor 104 and one voltage sensor 108 with a microcontroller 110 that continuously monitors the status of a cell array 106 within the battery pack 102. The temperature sensor 104 tracks the thermal behavior of the cells, and the voltage sensor 108 measures electrical potential across each cell array 106. The microcontroller 110 receives the real-time inputs and uses pre-programmed logic or dynamic algorithms to adjust the charging or discharging rate accordingly. For instance, when the temperature rises beyond a safe threshold during charging, the microcontroller 110 reduces or halts the charging current to prevent overheating. Similarly, when voltage fluctuations indicate potential overcharging or cell imbalance, the system 100 regulates power flow to maintain safe operating conditions. Consequently, the adaptive operation improves thermal stability, prevents degradation of battery cells, and ensures a more balanced and efficient energy usage throughout the battery pack. Further, based on the real-time sensors data, the C-rate is computed and compared with each other. The C-rate comparison provides the minimum charging or discharging rates for the battery to perform in optimal condition. Furthermore, by monitoring both temperature and voltage via the C-rate simultaneously and controlling the power flow accordingly, the system 100 ensures that each cell array 106 remains within safe operating limits. Consequently, the adaptive control of the charging/discharging cycle reduces stress on battery cells, resulting in fewer charge-discharge cycles and slower capacity degradation over time. Therefore, the system leads to longer service intervals, reduced maintenance, and better overall battery performance.
In an embodiment, the microcontroller 110 is configured to receive voltage values of the at least one cell array 106 of the at least one battery pack 102. The microcontroller 110 is configured to receive voltage values from at least one cell array 106 in the battery pack 102 through voltage sensors 108 integrated within the system 100. The voltage sensors 108 continuously measure the voltage of individual cells or groups of cells and send real-time data to the microcontroller 110 via Analog-to-Digital Converters (ADCs). The microcontroller 110 processes the voltage values to determine the state of charge (SoC), cell balancing needs, and potential faults such as overvoltage, undervoltage, or imbalances between cells. The microcontroller 110 compares the measured voltages with predefined threshold values stored in memory or lookup tables. For instance, in case a cell voltage exceeds or falls below a critical limit, the microcontroller 110 initiates protective actions such as adjusting charge/discharge rates, activating cell balancing circuits, or triggering safety shutdowns to prevent battery damage. Furthermore, the techniques for voltage monitoring include continuous sampling, periodic polling, and event-driven alerts. The continuous sampling ensures real-time monitoring, and periodic polling reduces power consumption by measuring at set intervals. The event-driven monitoring triggers voltage checks only when predefined conditions (such as rapid voltage drops) occur. The advantages of continuous monitoring include preventing overcharging or deep discharging, optimizing charging efficiency, supporting cell balancing, and enhancing the overall reliability of the battery pack. By ensuring that voltage levels remain within safe operating limits, the microcontroller reduces stress on individual cells, minimizes thermal risks, and enables efficient energy distribution in electric vehicles.
In an embodiment, the microcontroller 110 is configured to compute a state of charge value based on the received voltage values and a no-load voltage value. The microcontroller 110 is configured to compute the State of Charge (SoC) of the battery pack 102 by analyzing the received voltage values from the cells and the no-load voltage value (open-circuit voltage). The no-load voltage is the voltage measured when the battery is not supplying or receiving current, serving as a reference point for SoC estimation. The microcontroller 110 processes real-time voltage data using predefined voltage vs. SoC characteristics stored in lookup tables. Further, by comparing the measured cell voltage under load with the no-load voltage, the microcontroller 110 assesses the SoC estimation to account for internal resistance losses and dynamic variations due to charging or discharging. Additionally, temperature compensation algorithms adjust the voltage-based SoC calculations, ensuring accuracy across different operating conditions. Furthermore, the methods used to compute SoC include, but not limited to, voltage-based estimation, coulomb counting (current integration), and hybrid approaches. The voltage-based estimation relies on the open-circuit voltage (OCV) to determine SoC. The coulomb counting tracks charge/discharge currents over time with periodic recalibration. The hybrid method combines both above-mentioned techniques, enhancing accuracy by correcting cumulative current measurements with voltage-based data. The advantages of the SoC include preventing over-discharge, optimizing charging efficiency, enabling accurate range predictions for EVs, and supporting smart energy management systems. Further, by integrating voltage and no-load voltage values, the microcontroller 110 ensures reliable SoC calculations, improving the safety, efficiency, and lifespan of the battery pack.
In an embodiment, the microcontroller 110 is configured to receive temperature values for the computed state of charge value. The microcontroller is 110 configured to receive temperature values for refining the computed State of Charge (SoC) value of the battery pack 102. Specifically, the battery performance and voltage characteristics are temperature-dependent, as a given voltage level corresponds to different SoC values at different temperatures. The microcontroller 110 collects real-time temperature data from sensors embedded within the battery pack 102 and adjusts the SoC computation accordingly. The process involves applying temperature compensation algorithms, which modify the voltage-to-SoC mapping based on predefined temperature correction factors stored in lookup tables. The microcontroller 110 ensures that SoC estimation remains accurate across varying operating conditions, preventing errors caused by temperature fluctuations during charging, discharging, or idle states. Further, the temperature-compensated voltage-based method adjusts open-circuit voltage (OCV) readings via a temperature correction factor, improving accuracy in high or low temperature conditions. Furthermore, the hybrid method integrates Coulomb counting (tracking charge flow) with temperature-adjusted voltage readings to minimize cumulative errors. The advantages of the temperature values for SoC include preventing overcharging and deep discharging (which degrade battery health), optimizing energy distribution, ensuring safer battery operation in extreme temperatures, and extending battery lifespan. Further, by dynamically adjusting the SoC calculation based on real-time temperature input, the microcontroller 110 enables more reliable and efficient battery performance in electric vehicles.
In an embodiment, the microcontroller 110 is configured to identify a max-temperature value from the received temperature values. The microcontroller 110 is configured to identify the maximum temperature value from the received temperature readings of the battery pack 102. The system 100 continuously monitors temperature sensors placed across different cell arrays within the pack 102. The microcontroller 110 collects the real-time temperature values to determine the highest temperature value among all monitored points. The highest temperature is crucial for localized hotspots in the battery that indicate potential issues such as thermal runaway, cell imbalance, or excessive current draw. The microcontroller 110 utilizes the max-temperature value to trigger safety measures, such as derating the charging or discharging current, activating cooling systems, or even shutting down. Specifically, the direct comparison method involves probing all received sensor values and selecting the highest one for processing. The advantages of max-temperature identification include increased battery lifespan, prevention of thermal runaway incidents, enhanced system reliability, and optimized power output based on real-time temperature feedback.
In an embodiment, the microcontroller 110 is configured to compare the identified max-temperature value and the computed state of charge value with a lookup table, to derive a first C-rate limit. The microcontroller 110 is configured to compare the identified max-temperature value and the computed state of charge (SoC) value with a lookup table to determine a first C-rate limit for safe charging or discharging of the battery pack 102. The microcontroller 110 continuously receives temperature values from multiple sensors across the battery pack 102, identifies the max-temperature value, and computes the SoC value based on voltage readings and a no-load voltage reference. The two parameters, namely, temperature and SoC, are mapped to a predefined lookup table stored in the system’s memory. The lookup table contains C-rate limits corresponding to different SoC and temperature conditions. The microcontroller 110 cross-references the current SoC and max-temperature values with the table to derive the first C-rate limit, ensuring that the battery operates within a safe thermal and charge state window. The method for the comparison includes a direct lookup method involving matching the exact SoC and temperature values to predefined C-rate values. Further, an interpolation method is used for the measured values falling between two lookup table entries, allowing for a more accurate C-rate estimation. The advantages of the comparison with a look-up table include preventing thermal runaway, optimizing charge cycles, extending battery lifespan, and improving energy efficiency.
In an embodiment, the microcontroller 110 is configured to compute a delta cell voltage based on the received voltage values. The microcontroller 110 is configured to compute a delta cell voltage based on the received voltage values from individual battery cells within the pack 102. The microcontroller 110 continuously receives real-time voltage measurements from cell voltage sensors 108 that monitor each cell or a group of cells. The delta cell voltage is determined by identifying the difference between the highest and lowest cell voltage in the battery pack 102 at a given moment. The computation detects voltage imbalances, indicating cell degradation, overcharging, or an impending failure. The microcontroller 110 performs the computation at regular intervals and logs the delta voltage trend to assess the health and stability of the battery pack over time. The technique for computing delta cell voltage includes the direct subtraction method, involving finding the highest and lowest cell voltage values in the pack and computing the difference. Further, a statistical approach involves analyzing voltage distributions across all cells and setting a threshold for acceptable variance. The advantages of computing delta cell voltage include enhanced battery longevity, improved charging efficiency, and reduced risk of cell failures or thermal runaway. Further, by monitoring delta cell voltage, the microcontroller 110 implements corrective actions, such as triggering battery balancing mechanisms, issuing alerts, or adjusting charging and discharging rates to maintain optimal battery performance.
In an embodiment, the microcontroller 110 is configured to compare the computed delta cell voltage with a threshold delta cell voltage and compute a second C-rate limit based on the comparison. The microcontroller 110 is configured to compare the computed delta cell voltage with a predefined threshold delta cell voltage to determine the voltage imbalances in the battery pack 102. The microcontroller 110 receives the voltage values from individual cells through voltage sensors 108 and computes the delta cell voltage by determining the difference between the highest and lowest cell voltage. The computed delta cell voltage is compared with a predefined threshold stored in memory or a look-up table. Further, the exceedance of the computed delta cell voltage with respect to the threshold indicates cell imbalance, degradation, or uneven charging/discharging rates. Based on the comparison, the microcontroller 110 computes a second C-rate limit, which adjusts the charging or discharging rate to prevent excessive stress on the battery cells and avoid safety risks such as overheating or overcharging. Specifically, the dynamic adaptation method uses historical voltage trends to adjust the threshold adaptively based on battery conditions. The advantages of the comparison include preventing premature cell failure, improving safety, enabling efficient battery balancing, and enhancing the vehicle’s range and performance. Further, by actively controlling the C-rate based on voltage imbalances, the microcontroller 110 maintains uniform cell performance, reducing maintenance costs and ensuring stable and safe battery operation.
In an embodiment, the microcontroller 110 is configured to compute a delta cell temperature based on the received temperature value. The microcontroller 110 is configured to compute a delta cell temperature by processing the received temperature values from multiple sensors placed across the battery pack 102. The microcontroller 110 receives the temperature readings from individual cells or cell groups and computes the delta cell temperature as the difference between the maximum and minimum cell temperatures. The computed delta value determines the thermal imbalances within the battery pack 102 occurring due to uneven charge/discharge rates, thermal runaway risks, or inefficient cooling. The microcontroller 110 continuously monitors the values and triggers necessary control actions such as adjusting cooling mechanisms, modifying power flow, or limiting the charging/discharging rate to ensure thermal stability. The advantages of the computation of the delta cell temperature include optimized performance, reduced risk of thermal runaway, efficient energy distribution, and extended battery life, leading to greater reliability and stability in the battery pack 102.
In an embodiment, the microcontroller 110 is configured to compare the computed delta cell temperature with a threshold delta temperature and compute a third C-rate limit based on the comparison. The microcontroller 110 is configured to compare the computed delta cell temperature with a predefined threshold delta temperature to determine the thermal imbalances in the battery pack 102. The microcontroller 110 receives the temperature values from temperature sensors 104 positioned across multiple battery cells and computes the delta cell temperature as the difference between the maximum and minimum cell temperatures. Subsequently, the microcontroller 110 retrieves a threshold delta temperature from a stored lookup table or predefined safety limits and compares it with the computed delta cell temperature. The exceedance of the computed delta cell temperature with respect to the threshold indicates thermal imbalance leading to uneven aging, overheating, or thermal runaway. Based on the comparison, the microcontroller 110 computes a third C-rate limit, which reduces the charging or discharging rate to prevent excessive temperature variation within the battery pack 102. Different methods for the comparison include a fixed threshold method that applies a predefined safety limit after which derating is enforced. The second method, namely the adaptive threshold method, dynamically adjusts the limit based on factors such as ambient temperature, cell aging, and historical performance data to improve efficiency. The advantages include preventing localized overheating, reducing the risk of thermal runaway, optimizing thermal management, and extending the battery lifespan, leading to improved efficiency and safety in battery pack 102.
In an embodiment, the microcontroller 110 is configured to compare the first C-rate limit, the second C-rate limit, and the third C-rate limit to compute a minimum C-rate limit based on the comparison. Specifically, the microcontroller 110 processes real-time data from sensors to measure state of charge (SoC), temperature, and voltage. Firstly, the first C-rate limit is derived from a lookup table based on SoC and temperature, ensuring the battery operates within safe limits. Secondly, the second C-rate limit is computed by comparing the delta cell voltage (voltage imbalance between the highest and lowest cells) against a threshold delta cell voltage, and in case the imbalance exceeds a critical threshold, the C-rate is restricted to prevent overcharging or over-discharging. Thirdly, the third C-rate limit is determined by analyzing the delta cell temperature (temperature imbalance between the hottest and coolest cells) and comparing the third C-rate limit with a threshold delta temperature. In case the thermal imbalance is above the threshold, the charging/discharging is limited to prevent localized overheating and thermal runaway. Subsequently, the microcontroller 110 compares all three C-rate limits and selects the minimum value as the final operating C-rate to ensure optimal battery safety and efficiency. The minimum C-rate value provides the minimum value as of the charging or discharging rate, and thereby, subsequently, the delta cell voltage and the delta cell temperature are contained in the operational range. Further, the minimum C-rate is computed via various methods. Specifically, the real-time comparison method continuously monitors C-rate parameters and dynamically selects the lowest permissible value. The algorithmic decision-making method applies predefined rules to determine the safe operating limit by prioritizing the most restrictive constraint. The weighted average method assigns different weight levels to each C-rate limit to achieve a more adaptive approach. The advantages of the minimum C-rate value computation include improved battery lifespan, better thermal stability, reduced risk of cell imbalance, and increased overall efficiency. By automatically adjusting the charging and discharging rates based on real-time conditions, the system 100 prevents overloading and overheating, ensuring the battery operates safely and efficiently under varying operational conditions.
In an embodiment, based on the minimum C-rate limit, the microcontroller 110 is configured to generate a first instruction signal to control the charging rate and a second instruction signal to control the discharging rate. The microcontroller 110 is configured to generate a first instruction signal and a second instruction signal based on the minimum C-rate limit, ensuring optimal battery performance and safety. The microcontroller 110 receives and processes multiple derating factors, including the state of charge (SoC), max temperature, delta cell voltage, and delta cell temperature. The minimum C-rate limit is determined by selecting the lowest value among the first C-rate limit (SoC and max temperature-based), the second C-rate limit (delta cell voltage-based), and the third C-rate limit (delta cell temperature-based). As the minimum C-rate limit is computed, the microcontroller 110 generates a first instruction signal to regulate the charging rate and a second instruction signal to control the discharging rate. The signals are sent to the battery management system (BMS), motor controller, or power distribution unit (PDU) to ensure that charging/discharging remains within safe operational boundaries. Further, the first instruction signal, and the second instruction signal are generated via various methods. In the direct signal control method, the microcontroller 110 sends a PWM (pulse-width modulation) or CAN (Controller Area Network) bus signal to the BMS and/or motor controller, adjusting the power flow accordingly. The adaptive control method continuously adjusts the signals based on real-time feedback from the battery sensors, allowing for more dynamic power management. The advantages of the first instruction signal and the second instruction signal include preventing battery overheating, reducing excessive wear and degradation, improving energy efficiency, enhancing battery lifespan, and optimizing vehicle performance. By dynamically adjusting power output, the system ensures reliable and safe battery operation in various environmental and operating conditions.
In an embodiment, the microcontroller 110 is configured to send the first instruction signal to a charging source 112 and the second instruction signal to a load power controller 114. The microcontroller 110 is configured to send the first instruction signal to a charging source 112 and the second instruction signal to a load power controller 114 based on the minimum C-rate limit. The microcontroller 110 processes real-time data from various sensors, including voltage sensors 108 and temperature sensors 104, to determine individual C-rate limits. After computing the minimum C-rate limit, the microcontroller 110 generates two distinct instruction signals. The first instruction signal is sent to the charging source 112, such as, but not limited to, an onboard charger or external power supply, to regulate the charging current and voltage according to the safe operational range of the battery pack 102. Similarly, the second instruction signal is sent to the load power controller 114, which manages the discharge power sent to the motor or auxiliary systems, ensuring that the discharge rate does not exceed the safe threshold. The control mechanisms prevent overcharging, thermal runaway, and excessive power draw, thereby ensuring the longevity and reliability of the battery pack. The pulse-width modulation (PWM) method allows fine-tuned control over the charging and discharging currents by adjusting duty cycles. The CAN (Controller Area Network) communication method facilitates seamless integration with vehicle systems, transmitting C-rate limits and power regulation commands. The lookup table-based adaptive method dynamically adjusts the charging and discharging parameters based on predefined battery characteristics. The advantages of sending the first instruction signal to a charging source and the second instruction signal to a load power controller include enhanced battery lifespan, improved thermal management, prevention of sudden voltage fluctuations, increased vehicle efficiency, and improved safety during operation.
In accordance with a second aspect, there is described a method for controlling power flow of at least one battery pack, the method comprises:
- receiving voltage values corresponding to the at least one cell array to a microcontroller;
- comparing a first C-rate limit, a second C-rate limit, and a third C-rate limit, via the microcontroller;
- computing a minimum C-rate limit based on the comparison, via the microcontroller;
- generating a first instruction signal and a second instruction signal based on the computed minimum C-rate limit, via the microcontroller; and
- sending the first instruction signal to a charging source and the second instruction signal to the load power controller, via the microcontroller.
Figure 2 describes a method 200 for controlling power flow of a battery pack 102. The method 200 starts at a step 202. At the step 202, the method 200 comprises receiving voltage values corresponding to the at least one cell array to a microcontroller 110. At a step 204, the method 200 comprises comparing a first C-rate limit, a second C-rate limit, and a third C-rate limit, via a microcontroller 110. At a step 206, the method 200 comprises computing a minimum C-rate limit based on the comparison, via the microcontroller 110. At a step 208, the method 200 comprises generating a first instruction signal and a second instruction signal based on the computed minimum C-rate limit, via the microcontroller 110. At a step 210, the method 200 comprises sending the first instruction signal to a charging source and the second instruction signal to the load power controller, via the microcontroller 110.
In an embodiment, the method 200 comprises computing a state of charge value based on the received voltage values and a no-load voltage value via the microcontroller 110.
In an embodiment, the method 200 comprises receiving temperature values for the computed state of charge value to the microcontroller 110.
In an embodiment, the method 200 comprises identifying a max-temperature value from the received temperature values via the microcontroller 110.
In an embodiment, the method 200 comprises comparing the identified max-temperature value and the computed state of charge value with a lookup table, to derive a first C-rate limit via the microcontroller 110.
In an embodiment, the method 200 comprises computing a delta cell voltage based on the received voltage values via the microcontroller 110.
In an embodiment, the method 200 comprises comparing the computed delta cell voltage with a threshold delta cell voltage and computing a second C-rate limit based on the comparison via the microcontroller 110.
In an embodiment, the method 200 comprises computing a delta cell temperature based on the received temperature value via the microcontroller 110.
In an embodiment, the method 200 comprises comparing the computed delta cell temperature with a threshold delta temperature and computing a third C-rate limit based on the comparison via the microcontroller 110.
In an embodiment, the method 200 comprises computing a state of charge value based on the received voltage values and a no-load voltage value via the microcontroller 110. Further, the method 200 comprises receiving temperature values for the computed state of charge value. Furthermore, the method 200 comprises identifying a max-temperature value from the received temperature values. Furthermore, the method 200 comprises comparing the identified max-temperature value and the computed state of charge value with a lookup table, to derive a first C-rate limit via the microcontroller 110. Furthermore, the method 200 comprises computing a delta cell voltage based on the received voltage values via the microcontroller 110. Furthermore, the method 200 comprises comparing the computed delta cell voltage with a threshold delta cell voltage and computing a second C-rate limit based on the comparison via the microcontroller 110. Furthermore, the method 200 comprises computing a delta cell temperature based on the received temperature value via the microcontroller 110. Furthermore, the method 200 comprises comparing the computed delta cell temperature with a threshold delta temperature and computing a third C-rate limit based on the comparison via the microcontroller 110
In an embodiment, the method 200 comprises receiving voltage values corresponding to the at least one cell array to a microcontroller 110. Furthermore, the method 200 comprises comparing a first C-rate limit, a second C-rate limit, and a third C-rate limit, via a microcontroller 110. Furthermore, the method 200 comprises computing a minimum C-rate limit based on the comparison, via the microcontroller 110. Furthermore, generating a first instruction signal and a second instruction signal based on the computed minimum C-rate limit, via the microcontroller 110. Furthermore, the method 200 comprises sending the first instruction signal to a charging source and the second instruction signal to the load power controller, via the microcontroller 110.
Based on the above-mentioned embodiments, the present disclosure provides significant advantages of minimizing the damage to the battery by detecting falls or dropping the battery and providing a rapid response through the gate driver and switches, thereby optimizing the battery’s performance.
It would be appreciated that all the explanations and embodiments of the system 100 also apply mutatis-mutandis to the method 200.
In the description of the present invention, it is also to be noted that, unless otherwise explicitly specified or limited, the terms “disposed,” “mounted,” and “connected” are to be construed broadly, and may for example be fixedly connected, detachably connected, or integrally connected, either mechanically or electrically. They may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Modifications to embodiments and combinations of different embodiments of the present disclosure described in the foregoing are possible without departing from the scope of the present disclosure as defined by the accompanying claims. Expressions such as “including”, “comprising”, “incorporating”, “have”, and “is” used to describe and claim the present disclosure are intended to be construed in a non-exclusive manner, namely allowing for items, components or elements not explicitly described also to be present. Reference to the singular is also to be construed to relate to the plural where appropriate.
Although embodiments have been described with reference to a number of illustrative embodiments thereof, it should be understood that numerous other modifications and embodiments can be devised by those skilled in the art that will fall within the spirit and scope of the principles of this disclosure. More particularly, various variations and modifications are possible in the component parts and/or arrangements of the subject combination arrangement within the scope of the present disclosure, the drawings, and the appended claims. In addition to variations and modifications in the component parts and/or arrangements, alternative uses will also be apparent to those skilled in the art.
, Claims:WE CLAIM:
1. A system (100) for controlling power flow of at least one battery pack (102), the system (100) comprises:
- at least one temperature sensor (104) connected to at least one cell array (106) of the at least one battery pack (102);
- at least one voltage sensor (108) connected to the at least one cell array (106) of the at least one battery pack (102); and
- a microcontroller (110) communicably coupled with the at least one temperature sensor (104) and the at least one voltage sensor (108),
wherein the microcontroller (110) is configured to control charging or discharging rate of the at least one battery pack (102) based on inputs received from the at least one temperature sensor (104) and the at least one voltage sensor (108).

2. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to receive voltage values of the at least one cell array (106) of the at least one battery pack (102).

3. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to compute a state of charge value based on the received voltage values and a no-load voltage value.

4. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to receive temperature values for the computed state of charge value.

5. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to identify a max-temperature value from the received temperature values.

6. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to compare the identified max-temperature value and the computed state of charge value with a lookup table, to derive a first C-rate limit.

7. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to compute a delta cell voltage based on the received voltage values.

8. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to compare the computed delta cell voltage with a threshold delta cell voltage and compute a second C-rate limit based on the comparison.

9. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to compute a delta cell temperature based on the received temperature value.

10. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to compare the computed delta cell temperature with a threshold delta temperature and compute a third C-rate limit based on the comparison.

11. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to compare the first C-rate limit, the second C-rate limit, and the third C-rate limit to compute a minimum C-rate limit based on the comparison.

12. The system (100) as claimed in claim 1, wherein, based on the minimum C-rate limit, the microcontroller is configured to generate a first instruction signal to control the charging rate and a second instruction signal to control the discharging rate.

13. The system (100) as claimed in claim 1, wherein the microcontroller (110) is configured to send the first instruction signal to a charging source (112) and the second instruction signal to a load power controller (114).

14. A method (200) for controlling power flow of at least one battery pack (102), the method (200) comprising:
- receiving voltage values corresponding to the at least one cell array to a microcontroller (110);
- comparing a first C-rate limit, a second C-rate limit, and a third C-rate limit, via the microcontroller (110);
- computing a minimum C-rate limit based on the comparison, via the microcontroller (110);
- generating a first instruction signal and a second instruction signal based on the computed minimum C-rate limit, via the microcontroller (110); and
- sending the first instruction signal to a charging source and the second instruction signal to the load power controller, via the microcontroller (110).