DESC:METHOD AND SYSTEM FOR PREDICTING THERMAL RUNAWAY IN BATTERY PACKS
CROSS REFERENCE TO RELATED APPLICTIONS
The present application claims priority from Indian Provisional Patent Application No. 202321059001 filed on 03/09/2023, the entirety of which is incorporated herein by a reference.
TECHNICAL FIELD
The present disclosure generally relates to a battery thermal runaway detection. Particularly, the present disclosure relates to a system for detecting thermal runaway in battery packs. Furthermore, the present disclosure relates to a method of detecting thermal runaway in battery packs.
BACKGROUND
Nowadays, Electric vehicles (EVs) are increasingly used in daily life for commuting, errands, and travel, offering a clean and efficient alternative to traditional gasoline-powered cars. These electric vehicles are providing lower operating costs, reduced emissions, and quieter rides. Furthermore, the electric vehicle is a vehicle that uses an electric motor operated with electrical energy supplied from a battery. Recently, the lithium-ion battery is a type of rechargeable battery and the use of lithium-ion batteries in electric vehicles is increasing.
Along with the increasing demand of electric vehicles, the battery health is one of the crucial aspects which is important in terms of reliability of electric vehicle. The battery health monitoring is important for maintaining the performance, safety, and longevity of battery systems, especially in electric vehicles (EVs). Moreover, the battery health monitoring provides real-time insights into the battery’s condition, such as capacity, state of health (SOH), and potential degradation. By continuously tracking these metrics, battery health monitoring helps prevent unexpected failures, optimizes energy usage, and ensures safety by detecting early signs of issues like thermal runaway or capacity loss. It also aids in predictive maintenance, enabling timely interventions that extend the battery’s lifespan and ensure reliable performance throughout its service life.
Currently, detecting thermal runaway in electric vehicles (EVs) is critical for ensuring safety, as it involves a rapid, uncontrollable temperature increase that leads to battery failure. To prevent such incidents, multiple techniques are employed to monitor and detect early signs of thermal runaway in lithium-ion batteries. A temperature monitoring using thermocouples, RTDs, or thermistors strategically placed within the battery pack is a primary method, feeding data into the Battery Management System (BMS) to trigger protective measures if thresholds are exceeded. However, the present ways of temperature monitoring by itself might not be enough because thermal runaway may happen very quickly. Moreover, to enhance thermal runaway detection, a voltage and current monitoring are also used which detects the abnormal drops in voltage and changes in current flow and indicates the signals of early thermal issues. Furthermore, a gas detection sensors play a critical role by identifying gases like CO2, CO, and H2 released during overheating, serving as early warnings. Additionally, acoustic detection, an emerging technique, leverages the sound signatures produced by degrading batteries, with microphones capturing these signals for analysis. Moreover, an advanced machine learning algorithms are increasingly integrated into BMS to analyse data from these various sensors, identifying patterns that predict potential thermal runaway events. Altogether, these methods provide a comprehensive safety net, enhancing the ability of modern EVs to detect and prevent thermal runaway and ensuring the user safety. However, the present temperature monitoring may not always detect issues in time due to the rapid progression of thermal runaway. Also, the voltage and current monitoring may sometimes produce false positives, as fluctuations in these parameters can occur for reasons unrelated to thermal runaway. The gas detection sensors are effective but may be slow to respond, and the presence of gases not always correlate with an imminent threat which potentially leading to unnecessary alarms. Furthermore, the acoustic detection may struggle with accuracy in noisy environments, and it is not yet widely adopted which making it less reliable as a runaway detection method. Moreover, machine learning algorithms, although powerful which require vast amounts of high-quality data and may not perform well in all scenarios, particularly in cases where the data is not structured.
Therefore, there exists a need for an improved thermal runaway detection mechanism that overcomes the one or more problems associated as set forth above.
SUMMARY
An object of the present disclosure is to provide a system for detecting thermal runaway in battery packs.
Another object of the present disclosure is to provide a method of detecting thermal runaway in battery packs.
In accordance with first aspect of the present disclosure, there is provided a system for detecting thermal runaway in battery packs. The system comprises a battery module and a battery management system. The battery module comprises a plurality of cell strings, a plurality of busbars, and a plurality of voltage sensors, wherein the plurality of voltage sensors are configured to monitor voltage data in the battery module. The battery management system is configured to receive the voltage data from the plurality of voltage sensors, calculate a plurality of voltage differentials based on the received voltage data, compare the calculated plurality of voltage differentials to respective threshold values, calculate a plurality of rates of voltage change based on the received voltage data, analyse the plurality of rates of voltage change to detect anomalies, correlate the voltage data with a temperature data of the battery module, generate alerts based on the comparisons, detected anomalies and correlations, and determine a thermal runaway condition based on a combination of the generated alerts.
The present disclosure provides a system for the thermal runaway detection battery packs. Advantageously, the system enhances the safety of an electric vehicle by preventing battery thermal runaways. Moreover, the system is beneficial in terms of early identification of potential thermal runaways in the battery packs. Moreover, the system beneficially reduces the risk of fires or explosions in the battery packs. Moreover, the system beneficially prevents battery pack from overheating. Beneficially, the system of the present disclosure is reliable in accurately detecting thermal runaways. Beneficially, the system of the present disclosure utilizes separate monitoring and triggers for different operational conditions such as charging state, discharging state or idle state of the battery pack. Beneficially, the system of the present disclosure is advantageous in terms of preventing false alerts. Beneficially, the false alerts are prevented by correlating different triggers generated based on different parameters.
In accordance with second aspect of the present disclosure, there is provided a method of detecting thermal runaway in battery packs. The method comprises receiving the voltage data from the plurality of voltage sensors, calculating a plurality of voltage differentials based on the received voltage data, comparing the calculated plurality of voltage differentials to respective threshold values, calculating a plurality of rates of voltage change based on the received voltage data, analysing the plurality of rates of voltage change to detect anomalies, correlating the voltage data with a temperature data of the battery module, generating alerts based on the comparisons, detected anomalies and correlations, determining a thermal runaway condition based on a combination of the generated alerts.
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:
FIG. 1 illustrates a block diagram of a system for detecting thermal runaway in battery packs, in accordance with an aspect of the present disclosure.
FIG. 2 illustrates a flow chart of a method of detecting thermal runaway in battery packs, in accordance with another aspect 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 recognise that other embodiments for carrying out or practising the present disclosure are also possible.
The description set forth below in connection with the appended drawings is intended as a description of certain embodiments of a system and method for detecting thermal runaway in battery packs and is not intended to represent the only forms that may be developed or utilised. The description sets forth the various structures and/or functions in connection with the illustrated embodiments; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimised to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present invention.
While the disclosure is susceptible to various modifications and alternative forms, specific embodiment thereof has been shown by way of example in the drawings and will be described in detail below. It should be understood, however, that it is not intended to limit the disclosure to the particular forms disclosed, but on the contrary, the disclosure is to cover all modifications, equivalents, and alternatives falling within the scope of the disclosure.
The terms “comprise”, “comprises”, “comprising”, “include(s)”, or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a setup, system that comprises a list of components or steps does not include only those components or steps but may include other components or steps not expressly listed or inherent to such setup or system. In other words, one or more elements in a system or apparatus preceded by “comprises... a” does not, without more constraints, preclude the existence of other elements or additional elements in the system or apparatus.
In the following detailed description of the embodiments of the disclosure, reference is made to the accompanying drawings and which are shown by way of illustration specific embodiments in which the disclosure may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the disclosure, and it is to be understood that other embodiments may be utilized and that changes may be made without departing from the scope of the present disclosure. The following description is, therefore, not to be taken in a limiting sense.
The present disclosure will be described herein below with reference to the accompanying drawings. In the following description, well known functions or constructions are not described in detail since they would obscure the description with unnecessary detail.
As used herein, the terms ‘electric vehicle’, ‘EV’, and ‘EVs’ are used interchangeably and refer to any vehicle having stored electrical energy, including the vehicle capable of being charged from an external electrical power source. This may include vehicles having batteries which are exclusively charged from an external power source, as well as hybrid-vehicles which may include batteries capable of being at least partially recharged via an external power source. Additionally, it is to be understood that the ‘electric vehicle’ as used herein includes electric two-wheeler, electric three-wheeler, electric four-wheeler, electric pickup trucks, electric trucks and so forth.
As used herein, the term ‘battery pack’ refers to multiple individual battery cells connected together to provide a higher combined voltage or capacity than what a single battery can offer. The battery pack is designed to store electrical energy and supply it as needed to various devices or systems. Battery pack, as referred herein may be used for various purposes such as power electric vehicles and other energy storage applications. Furthermore, the battery pack may include additional circuitry, such as a battery management system (BMS), to ensure the safe and efficient charging and discharging of the battery cells. The battery pack comprises a plurality of cell strings which in turn comprises a plurality of battery cells.
As used herein, the term ‘battery module’ refers to subunit of battery pack comprising the combination of multiple individual battery cells connected together to provide a higher combined voltage or capacity than what a single cell can offer.
As used herein, the term ‘busbar’ refers to a conductive metal strip or plate used to facilitate the distribution of electrical power or signals within the cell array. The bus bar plate serves as a common electrical connection point for multiple battery cells.
As used herein, the term ‘cell string’ refers to an assembled unit of a plurality of cylindrical battery cells that are connected together physically and electrically to form a larger energy storage system. Each cell within the string is typically a discrete unit capable of storing electrical energy. The cell strings can be arranged in series or parallel configuration depending on the desired voltage and capacity requirements. It is understood that connecting cell strings in series increases the overall voltage of the battery pack, while connecting them in parallel increases the capacity. The electrical connections in the cell string are formed by connecting the terminals of the battery cells with bus bars. Furthermore, in addition to the individual cells, a battery pack may also include circuitry for balancing the charge levels of the cells, managing the charging and discharging processes, and providing safety features such as overcharge and over-discharge protection. The cell string, along with the associated electronics and packaging, forms the core component of a battery pack, enabling the efficient and reliable storage and delivery of electrical energy.
As used herein, the term ‘battery management system’ refers to an electronic control unit that monitors and manages the performance of the battery module. The battery management system is crucial for ensuring a battery module operates within safe limits, optimizes its performance, and extends its lifespan. The battery management system performs, monitoring, protection, balancing and communication operations in the battery pack. The battery management system may include a control unit to perform various operations.
As used herein, the term ‘brick’ refers to a combination of cell strings forming discrete unit of battery module. It is to be understood that multiple bricks are combined to form the battery module.
As used herein, the terms ‘control unit’, ‘processing arrangement’ and ‘processor’ are used interchangeably and refer to a computational element that is operable to respond to and processes instructions that operate the system. Optionally, the control unit includes, but is not limited to, a microprocessor, a micro-controller, a complex instruction set computing (CISC) microprocessor, a reduced instruction set (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or any other type of processing circuit. Furthermore, the term “processor” may refer to one or more individual processors, processing devices and various elements associated with a processing device that may be shared by other processing devices. Furthermore, the control unit may comprise ARM Cortex-M series processors, such as the Cortex-M4 or Cortex-M7, or any similar processor designed to handle real-time tasks with high performance and low power consumption. Furthermore, the control unit may comprise custom and/or proprietary processors.
As used herein, the term ‘communicably coupled’ refers to a bi-directional connection between the various components of the system. The bi-directional connection between the various components of the system enables exchange of data between two or more components of the system. Similarly, bi-directional connection between the system and other elements/modules enables exchange of data between system and the other elements/modules.
As used herein, the term ‘voltage sensor’ refers to a sensor responsible for monitoring the voltage of the battery cells, which is a critical factor in ensuring safe and efficient operation.
Figure 1, in accordance with an embodiment describes a system 100 for detecting thermal runaway in battery packs. The system 100 comprises a battery module 102 and a battery management system 110. The battery module 102 comprises a plurality of cell strings 104, a plurality of busbars 106, and a plurality of voltage sensors 108, wherein the plurality of voltage sensors 108 are configured to monitor voltage data in the battery module 102. The battery management system 110 is configured to receive the voltage data from the plurality of voltage sensors 108, calculate a plurality of voltage differentials based on the received voltage data, compare the calculated plurality of voltage differentials to respective threshold values, calculate a plurality of rates of voltage change based on the received voltage data, analyse the plurality of rates of voltage change to detect anomalies, correlate the voltage data with a temperature data of the battery module 102, generate alerts based on the comparisons, detected anomalies and correlations, and determine a thermal runaway condition based on a combination of the generated alerts.
The present disclosure provides a system 100 for the thermal runaway detection battery packs. Advantageously, the system 100 enhances the safety of an electric vehicle by preventing battery thermal runaways. Moreover, the system 100 is beneficial in terms of early identification of potential thermal runaways in the battery packs. Moreover, the system 100 beneficially reduces the risk of fires or explosions in the battery packs. Moreover, the system 100 beneficially prevents battery pack from overheating. Beneficially, the system 100 of the present disclosure is reliable in accurately detecting thermal runaways. Beneficially, the system 100 of the present disclosure utilizes separate monitoring and triggers for different operational conditions such as charging state, discharging state or idle state of the battery pack. Beneficially, the system 100 of the present disclosure is advantageous in terms of preventing false alerts. Beneficially, the false alerts are prevented by correlating different triggers generated based on different parameters.
It is to be understood that the plurality of voltage sensors 108 are distributed inside the battery module 102 at various physical locations. Furthermore, the plurality of voltage sensors 108 are communicably coupled to the battery management system 110.
In an embodiment, the battery management system 110 is configured to calculate a delta voltage as a difference between a maximum and minimum voltage among all voltage sensors in the battery module 102, to calculate the plurality of voltage differentials. Beneficially, the delta voltage is the difference between the maximum and minimum voltages recorded by all sensors in the battery module.
In an embodiment, the battery management system 110 is configured to compare the delta voltage to a first threshold value, when the delta voltage exceeds the first threshold value compare a maximum temperature in the battery pack to a temperature threshold, and when both the delta voltage and maximum temperature exceed their respective thresholds generate a voltage-temperature anomaly alert. Beneficially, the differential is compared to the predetermined threshold. If it exceeds the threshold and the maximum temperature also exceeds the temperature threshold, the voltage-temperature anomaly alert is generated.
In an embodiment, the battery management system 110 is configured to calculate a rate of change of voltage at predetermined intervals, and calculate a deviation in the rate of change of voltage over a predetermined time period to calculate rates of voltage change. In an embodiment, the battery management system 110 is configured to compare the deviation in the rate of change of voltage to a threshold value, and generate a high voltage change alert, when the deviation in the rate of change of voltage exceeds the threshold value. Beneficially, if the deviation exceeds a threshold, the high voltage change alert is generated.
In an embodiment, the battery management system 110 is configured to monitor the battery module 102 during a discharge state and when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold check a temperature trend over a predetermined time period, and when the temperature trend indicates a sustained temperature increase, generate a discharge state thermal runaway alert.
In an embodiment, the battery management system 110 is configured to monitor the battery module 102 during a charge state and when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold check a temperature trend over a predetermined time period, and when the temperature trend indicates a sustained temperature increase, generate a charge state thermal runaway alert.
Beneficially, the correlation between the voltage and temperature helps in identifying potential thermal issues that may not be apparent from voltage or temperature data alone.
In an embodiment, the battery management system 110 is configured to detect a failure in one or more voltage sensors 108 by monitoring for continuous high readings, drastic variations, or continuous low readings from each voltage sensor. In an embodiment, the battery management system 110 is configured to substitute the failed sensor's value with a calculated value based on readings from functioning sensors, when the sensor failure is detected. Beneficially, the failure detection and substitution of the failed sensor's value increases the robustness of the system 100 and reduces the risk of detection failure due to minor sensor failures.
In an embodiment, the battery management system 110 is configured to adapt the threshold values based on at least one of: battery module age, battery module usage history, environmental conditions, or charging/discharging state of the battery module 102. Beneficially, the adapted threshold values enable the system 100 to accurately detect the battery thermal runaway throughout the operational life of the battery pack.
In an embodiment, the system 100 for detecting thermal runaway in battery packs. The system 100 comprises the battery module 102 and the battery management system 110. The battery module 102 comprises the plurality of cell strings 104, the plurality of busbars 106, and the plurality of voltage sensors 108, wherein the plurality of voltage sensors 108 are configured to monitor voltage data in the battery module 102. The battery management system 110 is configured to receive the voltage data from the plurality of voltage sensors 108, calculate the plurality of voltage differentials based on the received voltage data, compare the calculated plurality of voltage differentials to respective threshold values, calculate the plurality of rates of voltage change based on the received voltage data, analyse the plurality of rates of voltage change to detect anomalies, correlate the voltage data with the temperature data of the battery module 102, generate alerts based on the comparisons, detected anomalies and correlations, and determine the thermal runaway condition based on the combination of the generated alerts. Furthermore, the battery management system 110 is configured to calculate the delta voltage as the difference between the maximum and minimum voltage among all voltage sensors in the battery module 102, to calculate the plurality of voltage differentials. Furthermore, the battery management system 110 is configured to compare the delta voltage to the first threshold value, when the delta voltage exceeds the first threshold value compare the maximum temperature in the battery pack to the temperature threshold, and when both the delta voltage and maximum temperature exceed their respective thresholds generate the voltage-temperature anomaly alert. Furthermore, the battery management system 110 is configured to calculate the rate of change of voltage at predetermined intervals, and calculate the deviation in the rate of change of voltage over the predetermined time period to calculate rates of voltage change. Furthermore, the battery management system 110 is configured to compare the deviation in the rate of change of voltage to the threshold value, and generate the high voltage change alert, when the deviation in the rate of change of voltage exceeds the threshold value. Furthermore, the battery management system 110 is configured to monitor the battery module 102 during the discharge state and when the delta voltage exceeds the threshold value and the maximum temperature exceeds the temperature threshold check the temperature trend over the predetermined time period, and when the temperature trend indicates the sustained temperature increase, generate the discharge state thermal runaway alert. Furthermore, battery management system 110 is configured to monitor the battery module 102 during the charge state and when the delta voltage exceeds the threshold value and the maximum temperature exceeds the temperature threshold check the temperature trend over the predetermined time period, and when the temperature trend indicates the sustained temperature increase, generate the charge state thermal runaway alert. Furthermore, the battery management system 110 is configured to detect the failure in one or more voltage sensors 108 by monitoring for continuous high readings, drastic variations, or continuous low readings from each voltage sensor. Furthermore, the battery management system 110 is configured to substitute the failed sensor's value with the calculated value based on readings from functioning sensors, when the sensor failure is detected. Furthermore, the battery management system 110 is configured to adapt the threshold values based on at least one of: battery module age, battery module usage history, environmental conditions, or charging/discharging state of the battery module 102.
In an exemplary embodiment, the voltage monitoring interval may be 250 milliseconds. In an alternative embodiment, the voltage monitoring interval may be any other suitable time interval. In an embodiment, the delta voltage threshold may be 0.3 V for pre-charge state and charging/discharging state. In an alternative embodiment, the delta voltage threshold may be any other suitable voltage value for the different states. In an embodiment, the rate of change of voltage calculation interval may be 500 milliseconds. In an alternative embodiment, the rate of change of voltage calculation interval may be any other suitable time interval. In an embodiment, the deviation in rate of change of voltage calculation period may be 10 seconds. In an alternative embodiment, the deviation in rate of change of voltage calculation period may be any other suitable time period. In an embodiment, the minimum delta voltage between strings may be 0.2 V. In an alternative embodiment, the minimum delta voltage between strings may be any other suitable voltage value. In an embodiment, the temperature check interval during voltage anomalies may be 250 milliseconds. In an alternative embodiment, the temperature check interval during voltage anomalies may be any other suitable time interval. In an embodiment, the time period for temperature trend analysis may be 5 minutes. In an alternative embodiment, the time period for temperature trend analysis may be any other suitable time period. In an embodiment, during discharge state: Delta_V > 0.3V is checked along with Delta_T > 10°C and T_max > 70°C. In an embodiment, during charge state: Delta_V > 0.3V is checked along with Delta_T > 10°C and T_max > 55°C.
Figure 2, describes a method 200 of detecting thermal runaway in battery packs. The method 200 starts at step 202 and completes at step 216. At step 202, the method 200 comprises receiving the voltage data from the plurality of voltage sensors 108. At step 204, the method 200 comprises calculating a plurality of voltage differentials based on the received voltage data. At step 206, the method 200 comprises comparing the calculated plurality of voltage differentials to respective threshold values. At step 208, the method 200 comprises calculating a plurality of rates of voltage change based on the received voltage data. At step 210, the method 200 comprises analysing the plurality of rates of voltage change to detect anomalies. At step 212, the method 200 comprises correlating the voltage data with a temperature data of the battery module 102. At step 214, the method 200 comprises generating alerts based on the comparisons, detected anomalies and correlations. At step 216, the method 200 comprises determining a thermal runaway condition based on a combination of the generated alerts.
In an embodiment, the method 200 comprises calculating a delta voltage as a difference between a maximum and minimum voltage among all voltage sensors in the battery module 102, to calculate the plurality of voltage differentials.
In an embodiment, the method 200 comprises comparing the delta voltage to a first threshold value, when the delta voltage exceeds the first threshold value comparing a maximum temperature in the battery pack to a temperature threshold, and when both the delta voltage and maximum temperature exceed their respective thresholds, generating a voltage-temperature anomaly alert.
In an embodiment, calculating rates of voltage change comprises calculating a rate of change of voltage at predetermined intervals, and calculating a deviation in the rate of change of voltage over a predetermined time period.
In an embodiment, method 200 comprises comparing the deviation in the rate of change of voltage to a threshold value, and generating a high voltage change alert when the deviation in the rate of change of voltage exceeds the threshold value.
In an embodiment, the method 200 comprises monitoring the battery module 102 during a discharge state and when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold checking a temperature trend over a predetermined time period, and when the temperature trend indicates a sustained temperature increase generating a discharge state thermal runaway alert.
In an embodiment, the method 200 comprises monitoring the battery module 102 during a charge state and when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold checking a temperature trend over a predetermined time period, and when the temperature trend indicates a sustained temperature increase generating a charge state thermal runaway alert.
In an embodiment, the method 200 comprises detecting a failure in one or more voltage sensors 108 by monitoring for continuous high readings, drastic variations, or continuous low readings from each voltage sensor.
In an embodiment, the method 200 comprises substituting the failed sensor's value with a calculated value based on readings from functioning sensors, when the sensor failure is detected.
In an embodiment, the method 200 comprises adapting the threshold values based on at least one of: battery module age, battery module usage history, environmental conditions, or charging/discharging state of the battery module 102.
It would be appreciated that all the explanations and embodiments of the portable device 100 also applies 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 combination 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”, “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 detecting thermal runaway in battery packs, comprising:
- a battery module (102) comprising a plurality of cell strings (104), a plurality of busbars (106), and a plurality of voltage sensors (108), wherein the plurality of voltage sensors (108) are configured to monitor voltage data in the battery module (102); and
- a battery management system (110) configured to:
- receive the voltage data from the plurality of voltage sensors (108);
- calculate a plurality of voltage differentials based on the received voltage data;
- compare the calculated plurality of voltage differentials to respective threshold values;
- calculate a plurality of rates of voltage change based on the received voltage data;
- analyse the plurality of rates of voltage change to detect anomalies;
- correlate the voltage data with a temperature data of the battery module (102);
- generate alerts based on the comparisons, detected anomalies and correlations; and
- determine a thermal runaway condition based on a combination of the generated alerts.
2. The system (100) as claimed in claim 1, wherein the battery management system (110) is configured to calculate a delta voltage as a difference between a maximum and minimum voltage among all voltage sensors in the battery module (102), to calculate the plurality of voltage differentials.
3. The system (100) as claimed in claim 1, wherein the battery management system (110) is configured to:
- compare the delta voltage to a first threshold value;
- when the delta voltage exceeds the first threshold value, compare a maximum temperature in the battery pack to a temperature threshold; and
- when both the delta voltage and maximum temperature exceed their respective thresholds, generate a voltage-temperature anomaly alert.
4. The system (100) as claimed in claim 1, wherein the battery management system (110) is configured to:
- calculate a rate of change of voltage at predetermined intervals; and
- calculate a deviation in the rate of change of voltage over a predetermined time period,
to calculate rates of voltage change.
5. The system (100) as claimed in claim 4, wherein the battery management system (110) is configured to:
- compare the deviation in the rate of change of voltage to a threshold value; and
- generate a high voltage change alert, when the deviation in the rate of change of voltage exceeds the threshold value.
6. The system (100) as claimed in claim 1, wherein the battery management system (110) is configured to:
- monitor the battery module (102) during a discharge state;
- when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold:
- check a temperature trend over a predetermined time period; and
- when the temperature trend indicates a sustained temperature increase, generate a discharge state thermal runaway alert.
7. The system (100) as claimed in claim 1, wherein the battery management system (110) is configured to:
- monitor the battery module (102) during a charge state;
- when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold:
- check a temperature trend over a predetermined time period; and
- when the temperature trend indicates a sustained temperature increase, generate a charge state thermal runaway alert.
8. The system (100) as claimed in claim 1, wherein the battery management system (110) is configured to detect a failure in one or more voltage sensors (108) by monitoring for continuous high readings, drastic variations, or continuous low readings from each voltage sensor.

9. The system (100) as claimed in claim 8, wherein the battery management system (110) is configured to substitute the failed sensor's value with a calculated value based on readings from functioning sensors, when the sensor failure is detected.
10. The system (100) as claimed in claim 1, wherein the battery management system (110) is configured to adapt the threshold values based on at least one of: battery module age, battery module usage history, environmental conditions, or charging/discharging state of the battery module (102).
11. A method (200) of detecting thermal runaway in battery packs, wherein the method (200) comprises:
- receiving the voltage data from the plurality of voltage sensors (108);
- calculating a plurality of voltage differentials based on the received voltage data;
- comparing the calculated plurality of voltage differentials to respective threshold values;
- calculating a plurality of rates of voltage change based on the received voltage data;
- analysing the plurality of rates of voltage change to detect anomalies;
- correlating the voltage data with a temperature data of the battery module (102);
- generating alerts based on the comparisons, detected anomalies and correlations; and
- determining a thermal runaway condition based on a combination of the generated alerts.
12. The method (200) as claimed in claim 11, wherein the method (200) comprises calculating a delta voltage as a difference between a maximum and minimum voltage among all voltage sensors in the battery module (102), to calculate the plurality of voltage differentials.
13. The method (200) as claimed in claim 11, wherein the method (200) comprises:
- comparing the delta voltage to a first threshold value;
- when the delta voltage exceeds the first threshold value, comparing a maximum temperature in the battery pack to a temperature threshold; and
- when both the delta voltage and maximum temperature exceed their respective thresholds, generating a voltage-temperature anomaly alert.
14. The method (200) as claimed in claim 11, wherein calculating rates of voltage change comprises:
- calculating a rate of change of voltage at predetermined intervals; and
- calculating a deviation in the rate of change of voltage over a predetermined time period.
15. The method (200) as claimed in claim 11, wherein the method (200) comprises:
- comparing the deviation in the rate of change of voltage to a threshold value; and
- generating a high voltage change alert, when the deviation in the rate of change of voltage exceeds the threshold value.
16. The method (200) as claimed in claim 11, wherein the method (200) comprises:
- monitoring the battery module (102) during a discharge state;
- when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold:
- checking a temperature trend over a predetermined time period; and
- when the temperature trend indicates a sustained temperature increase, generating a discharge state thermal runaway alert.
17. The method (200) as claimed in claim 11, wherein the method (200) comprises:
- monitoring the battery module (102) during a charge state;
- when the delta voltage exceeds a threshold value and a maximum temperature exceeds a temperature threshold:
- checking a temperature trend over a predetermined time period; and
- when the temperature trend indicates a sustained temperature increase, generating a charge state thermal runaway alert.
18. The method (200) as claimed in claim 11, wherein the method (200) comprises detecting a failure in one or more voltage sensors (108) by monitoring for continuous high readings, drastic variations, or continuous low readings from each voltage sensor.
19. The method (200) as claimed in claim 11, wherein the method (200) comprises substituting the failed sensor's value with a calculated value based on readings from functioning sensors, when the sensor failure is detected.
20. The method (200) as claimed in claim 11, wherein the method (200) comprises adapting the threshold values based on at least one of: battery module age, battery module usage history, environmental conditions, or charging/discharging state of the battery module (102).