Description:FIELD OF THE INVENTION

The present disclosure pertains to the field of electric vehicles and energy storage systems. More specifically, it relates to a management system designed to optimize the utilization of multiple energy storage devices (ESDs) within an electric vehicle. The invention encompasses both a system and a method for efficiently managing and distributing power among these ESDs to maximize the overall energy output and enhance the driving range of the electric vehicle. The system integrates hardware and software components to intelligently control the charging, discharging, and overall operation of the ESDs, contributing to improved energy efficiency and performance in electric vehicles.

BACKGROUND OF THE INVENTION

Electric vehicles have witnessed a surge in popularity driven by their environmental advantages and the increasing global emphasis on sustainable transportation. Despite their notable benefits, a persistent challenge confronting electric vehicles is the limitation on driving range, often imposed by factors such as battery capacity and charging infrastructure.

The advent of electric vehicles has led to a heightened focus on enhancing their operational efficiency and overcoming limitations related to energy storage. Recognizing the critical role of energy storage devices (ESDs) in the performance of electric vehicles, the invention addresses this challenge by introducing a sophisticated management technique/system. This system is specifically designed to maximize the energy output of an electric vehicle by efficiently managing multiple ESDs.

The proposed electronics system represents a significant advancement in the domain of electric vehicle technology. It provides a comprehensive solution to the driving range constraint by introducing intelligent management techniques for multiple ESDs within the vehicle. By doing so, the invention aims to optimize the utilization of energy storage resources and, consequently, enhance the overall performance and efficiency of electric vehicles.

In light of the evolving landscape of sustainable transportation, this invention stands at the forefront, offering a promising avenue for mitigating range limitations in electric vehicles. The integration of this management technique/system is poised to contribute significantly to the widespread adoption and acceptance of electric vehicles as a viable and sustainable mode of transportation. In view of the foregoing discussion, it is portrayed that there is a need to have a system and method for managing multiple energy storage devices to maximize the energy output of an electric vehicle.

SUMMARY OF THE INVENTION

The present disclosure seeks to provide an electronics system designed for electric vehicles, specifically targeting the management of multiple energy storage devices (ESD) to enhance the vehicle's driving range. The system optimizes the use of multiple battery packs in an electric vehicle to extend its operational range while ensuring efficient power distribution. The invention presents an electronics system for electric vehicles that efficiently manages multiple ESDs to enhance the driving range. The system employs a combination of hardware and software components, providing intelligent battery management, distribution, and optimal utilization of power from multiple battery sources. The proposed technique / system is smart and uses the on-board charging to enhance the overall operational performance of an electric vehicle. The idea is to intelligently and dynamically split the on-board ESDs of the electric vehicle in real-time into two groups. The first group provides the energy to drive the vehicle and the other one accumulates the energy that can be used later. The energy stored in the second group of ESDs is received from an on-board charging unit. This stored energy is utilized to enhance the overall operational [performance of the electric vehicle significantly. The selection of ESDs to be grouped for the purpose of driving or charging is done dynamically with the help of EMU which has an inherent intelligent to do so.

In an embodiment, an electronics system for managing multiple battery packs in an electric vehicle is disclosed. The system includes a. a plurality of energy storage devices (ESDs) integrated into an electric vehicle.
The system further includes a plurality of sensors strategically placed within each ESD to monitor a set of parameters selected from state of charge (SoC), state of health (SoH), temperature, and voltage.
The system further includes a central controller interconnected to the ESDs and sensors to process data received from ESD Management Units (EMUs), sensors, and other vehicle systems, the central controller employing an optimization technique to optimize power distribution among the ESDs.
The system further includes a communication device wirelessly connected to the central controller to employ state-of-the-art bidirectional communication protocols, including high-speed wired and wireless technologies selected from Controller Area Network (CAN), Ethernet, or Bluetooth, for seamless communication between the CPU and each battery pack.
The system further includes a user interface integrated into a vehicle's dashboard or infotainment system through the communication device, allowing driver to monitor and configure ESD management settings.
The system further includes an onboard charging unit, an electro-mechanical/electronic unit configured to charge the ESDs intelligently based on system requirements.
The system further includes one or more voltage balancing circuits featuring advanced passive or active balancing techniques, intelligently controlled by the CPU to address voltage differentials among individual battery cells within each pack; and
The system further includes a safety mechanism incorporating the latest advancements in sensing and actuation technologies to detect and respond to abnormal conditions promptly, including overvoltage, overcurrent, or overheating, ensuring the swift and secure isolation of affected battery packs.

In another embodiment, a method for managing energy in an electric vehicle is disclosed. The method includes integrating a plurality of energy storage devices (ESDs) into an electric vehicle.
The method further includes monitoring a set of parameters selected from state of charge (SoC), state of health (SoH), temperature, and voltage by strategically placing sensors within each ESD.
The method further includes collecting and transmitting real-time data from the ESD to a central controller by equipping each ESD with an ESD Management Unit (EMU) that communicates with the central controller.
The method further includes processing data received from the EMUs, sensors, and other vehicle systems with the central controller, using optimization techniques to optimize power distribution among the ESDs.
The method further includes monitoring and configuring ESD management settings by providing a User Interface for a driver.
The method further includes employing an On-board Charging Unit to intelligently and dynamically split the ESDs into two groups in real-time, where a first group provides energy to drive the vehicle and a second group accumulates energy for later use, with the selection of ESDs for driving or charging purposes dynamically determined by the EMU, thereby enhancing overall operational performance of the electric vehicle.

An object of the present disclosure is to extend the driving range of electric vehicles without necessitating substantial modifications to the vehicle's physical design.
Another object of the present disclosure is to extend the driving range of electric vehicles without imposing a substantial cost impact. By optimizing the utilization of energy storage resources and employing sophisticated techniques, the system aims to achieve improved efficiency without introducing prohibitive expenses, thereby promoting cost-effective electric vehicle operation.
Another object of the present disclosure is to focus on improving the longevity of the battery pack by implementing optimized usage and charging patterns. Through intelligent management techniques, the system aims to mitigate factors contributing to battery degradation, thereby enhancing the overall lifespan of the energy storage system.
Another object of the present disclosure is to enhance the user experience by providing real-time data visualization and configuration options.
Yet another object of the present invention is to deliver an expeditious and cost-effective method for managing energy in an electric vehicle.

To further clarify the advantages and features of the present disclosure, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which are illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail in the accompanying drawings.

BRIEF DESCRIPTION OF FIGURES

These and other features, aspects, and advantages of the present disclosure will become better understood when the following detailed description is read concerning the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:

Figure 1 illustrates a block diagram of an electronics system for managing multiple battery packs in an electric vehicle in accordance with an embodiment of the present disclosure;
Figure 2 illustrates a flow chart of a method for managing energy in an electric vehicle in accordance with an embodiment of the present disclosure; and
Figure 3 illustrates a schematic diagram of the system on an electric vehicle in accordance with an embodiment of the present disclosure.

Further, skilled artisans will appreciate those elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. For example, the flow charts illustrate the method in terms of the most prominent steps involved to help to improve understanding of aspects of the present disclosure. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the drawings by conventional symbols, and the drawings may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the drawings with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein.

DETAILED DESCRIPTION:

To promote an understanding of the principles of the invention, reference will now be made to the embodiment illustrated in the drawings and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates.

It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the invention and are not intended to be restrictive thereof.

Reference throughout this specification to “an aspect”, “another aspect” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Thus, appearances of the phrase “in an embodiment”, “in another embodiment” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.

The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such process or method. Similarly, one or more devices or sub-systems or elements or structures or components proceeded by "comprises...a" does not, without more constraints, preclude the existence of other devices or other sub-systems or other elements or other structures or other components or additional devices or additional sub-systems or additional elements or additional structures or additional components.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The system, methods, and examples provided herein are illustrative only and not intended to be limiting.

Embodiments of the present disclosure will be described below in detail concerning the accompanying drawings.

Referring to Figure 1, a block diagram of an electronics system for managing multiple battery packs in an electric vehicle is illustrated in accordance with an embodiment of the present disclosure. The system 100 includes a plurality of energy storage devices (ESDs) (104) integrated into an electric vehicle (102).

In an embodiment, a plurality of sensors (106) are strategically placed within each ESD (104) to monitor a set of parameters selected from state of charge (SoC), state of health (SoH), temperature, and voltage.

In an embodiment, a central controller (108) is interconnected to the ESDs and sensors (106) to process data received from ESD Management Units (EMUs), sensors (106), and other vehicle systems, the central controller (108) employing an optimization technique to optimize power distribution among the ESDs.

In an embodiment, a communication device (120) is wirelessly connected to the central controller to employ state-of-the-art bidirectional communication protocols, including high-speed wired and wireless technologies selected from Controller Area Network (CAN), Ethernet, or Bluetooth, for seamless communication between the CPU and each battery pack.

In an embodiment, a user interface (112) is integrated into a vehicle's dashboard (110) or infotainment system through the communication device, allowing driver to monitor and configure ESD management settings.

In an embodiment, an onboard charging unit (114), an electro-mechanical/electronic unit configured to charge the ESDs (104) intelligently based on system requirements.

In an embodiment, one or more voltage balancing circuits (116) featuring advanced passive or active balancing techniques, intelligently controlled by the CPU to address voltage differentials among individual battery cells within each pack.

In an embodiment, a safety mechanism (118) incorporating the latest advancements in sensing and actuation technologies to detect and respond to abnormal conditions promptly, including overvoltage, overcurrent, or overheating, ensuring the swift and secure isolation of affected battery packs.

In another embodiment, the system further comprises an ESD Management Unit (EMU) associated with each battery pack, the EMU is configured to communicate with the central controller (108), collect real-time data from the ESDs, and transmit the data to the central controller (108).

In another embodiment, the central controller (108) employs an optimization technique to optimize power distribution among the battery packs, wherein the optimization technique is selected from a dynamic load balancing technique for optimizing power distribution among the ESDs based on their state of charge, health, and other parameters, a predictive power management technique for forecasting energy demand and adjusting distribution of power accordingly; an adaptive charging technique for dynamically adjusting charging rates of individual ESDs (104) based on real-time conditions; a fault tolerance technique for identifying and isolating malfunctioning ESDs to ensure reliability and safety and a machine learning-based optimization technique for continuously learning and adapting to driving patterns, environmental conditions, and ESD characteristics to enhance long-term performance.

In one embodiment, a predictive maintenance unit utilizing machine learning algorithms to anticipate potential battery issues based on historical data and initiate preventive measures.
In one embodiment, an augmented thermal management unit that employs advanced sensor technologies, strategically placed heat sinks, and dynamically controlled cooling fans to maintain optimal operating temperatures for each battery pack under diverse and challenging conditions.
In one embodiment, a telematics module for seamless remote monitoring and control of electric vehicle battery packs, providing enhanced connectivity and compatibility with external entities such as advanced fleet management systems or evolving charging infrastructures.

In another embodiment, the user interface (112) provides real-time data visualization and configuration options.

In another embodiment, the central controller (108) intelligently and dynamically splits the onboard ESDs (104) into two groups in real-time, wherein a first group of ESDs provides energy to drive the vehicle (102) and other accumulating energy for later use.

In another embodiment, a second group of ESDs (104) receives stored energy from the onboard charging unit (114), enhancing overall operational performance of the electric vehicle (102).

In another embodiment, selection of the first and second ESDs for driving or charging is dynamically performed by the EMU, incorporating inherent intelligence for optimal energy management.

In another embodiment, the power distribution optimization, comprises a preprocessing module connected to the data acquisition module to preprocess real-time data from ESD Management Units (EMUs)data to eliminate noise and normalize the data to a common scale.
In one embodiment, a state evaluation module is connected to the preprocessing module to evaluate current state of each ESD based on received data, assessing overall health and performance of the ESDs (104).
In one embodiment, an energy demand forecasting module is connected to the state evaluation module to utilize historical data and machine learning techniques to forecast energy demand for upcoming driving cycle, and adjust forecasts based on real-time factors.
In one embodiment, an optimization module is connected to the energy demand forecasting module to employ optimization techniques to determine optimal power distribution among the ESDs (104).
In one embodiment, a dynamic adjustment module is connected to the optimization module to dynamically adjust power distribution based on changing conditions during the driving cycle, continuously monitor ESD parameters, and adjust distribution in response to changes in energy demand or ESD performance.
In one embodiment, a fault tolerance and mitigation module is connected to the dynamic adjustment module to implement fault tolerance mechanisms to identify and isolate malfunctioning ESDs (104), and mitigate impact of faults by redistributing power among healthy ESDs.
In one embodiment, a user interface (112) update module is connected to the fault tolerance and mitigation module to update the user interface (112) with real-time information on ESD status, power distribution, and system performance, and provide alerts or recommendations to the driver if needed.
In one embodiment, an adaptive learning module is connected to the user interface (112) update module to implement adaptive learning mechanisms to continuously improve optimization techniques based on historical performance data and incorporate machine learning models to adapt to evolving driving patterns and environmental conditions.

Figure 2 illustrates a flow chart of a method for managing energy in an electric vehicle (102) in accordance with an embodiment of the present disclosure. At step 202, method 200 includes integrating a plurality of energy storage devices (ESDs) into an electric vehicle (102).
At step 204, method 200 includes monitoring a set of parameters selected from state of charge (SoC), state of health (SoH), temperature, and voltage by strategically placing sensors (106) within each ESD.
At step 206, method 200 includes collecting and transmitting real-time data from the ESD to a central controller (108) by equipping each ESD with an ESD Management Unit (EMU) that communicates with the central controller (108).
At step 208, method 200 includes processing data received from the EMUs, sensors (106), and other vehicle systems with the central controller (108), using optimization techniques to optimize power distribution among the ESDs.
At step 210, method 200 includes monitoring and configuring ESD management settings by providing a user interface (112) for a driver.
At step 212, method 200 includes employing an On-board Charging Unit to intelligently and dynamically split the ESDs into two groups in real-time, where a first group provides energy to drive the vehicle and a second group accumulates energy for later use, with the selection of ESDs for driving or charging purposes dynamically determined by the EMU, thereby enhancing overall operational performance of the electric vehicle (102).

In another embodiment, the power distribution optimization comprises the steps of receiving real-time data from ESD Management Units (EMUs), including SoC, SoH, temperature, and voltage for each ESD, and collecting data from sensors monitoring relevant parameters in the vehicle and its surroundings. Then, preprocessing acquired data to eliminate noise and ensure accuracy, and normalizing the data to a common scale. Then, evaluating current state of each ESD based on received data, assessing an overall health and performance of the ESDs. Then, forecasting energy demand for an upcoming driving cycle, and adjusting forecasts based on real-time factors by utilizing historical data and machine learning techniques. Then, determining the optimal power distribution among the ESDs by employing optimization techniques. Then, adjusting power distribution based on changing conditions during driving cycle, continuously monitoring ESD parameters, and adjusting distribution in response to changes in energy demand or ESD performance. Then, identifying and isolating malfunctioning ESDs, and mitigating impact of faults by redistributing power among healthy ESDs upon implementing fault tolerance mechanisms. Then, updating the user interface (112) with real-time information on ESD status, power distribution, and system performance, and providing alerts or recommendations to the driver if needed. Thereafter, implementing adaptive learning mechanisms to continuously improve optimization techniques based on historical performance data and incorporating machine learning models to adapt to evolving driving patterns and environmental conditions.
Figure 3 illustrates a schematic diagram of the system on an electric vehicle in accordance with an embodiment of the present disclosure. The enhanced range electric vehicle battery management system includes the following key components:
1. ESD Configuration: The system allows for multiple ESDs to be integrated into the electric vehicle (102). These ESDs may differ in capacity, chemistry, or age.
2. Sensor Network: Sensors are strategically placed within each ESD to monitor parameters such as state of charge (SoC), state of health (SoH), temperature, and voltage.
3. ESD Management Unit (EMU): Each battery pack is equipped with an EMU that communicates with a central controller (108). The EMUs collect and transmit data from the ESDs to the central controller (108) in real-time.

4. Central Controller: The core of the system, the central controller (108), processes data from the EMUs, sensors, and other vehicle systems. It employs sophisticated techniques to optimize power distribution among the ESDs.

5. User Interface: The system includes a user interface, typically integrated into the vehicle's dashboard (110) or infotainment system, allowing the driver to monitor and configure ESD management settings.
6. On-board charging unit: An electro-mechanical/electronic unit meant for charging the ESD.

The enhanced range electric vehicle battery management system provides a novel solution for managing multiple ESDs in electric vehicles, resulting in an extended driving range and improved user experience. The invention introduces a unique combination of hardware and software components, offering a substantial advantage to the electric vehicle industry.

The electronics system for managing multiple battery packs in an electric vehicle (102) comprises the central controller (108) for receiving and processing data from EMU and sensors. The plurality of ESDs, each equipped with an EMU. The user interface for monitoring and configuring ESD management settings. The on-board charging unit which charges the ESD(s) intelligently based on system requirements. The central controller (108) employs techniques to optimize power distribution among the battery packs. The user interface provides real-time data visualization and configuration options. The proposed system significantly reduces the need for charging the electric vehicle multiple times a day. The proposed system will help to reduce the overall carbon footprint significantly. The proposed system will enhance the overall efficiency of the electric vehicle ecosystem.

The drawings and the forgoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, orders of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts necessarily need to be performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples. Numerous variations, whether explicitly given in the specification or not, such as differences in structure, dimension, and use of material, are possible. The scope of embodiments is at least as broad as given by the following claims.

Benefits, other advantages, and solutions to problems have been described above about specific embodiments. However, the benefits, advantages, solutions to problems, and any component(s) that may cause any benefit, advantage, or solution to occur or become more pronounced are not to be construed as a critical, required, or essential feature or component of any or all the claims. , Claims:1. An electronics system for managing multiple battery packs in an electric vehicle, said system comprises:
a. a plurality of energy storage devices (ESDs) integrated into an electric vehicle;
b. a plurality of sensors strategically placed within each ESD to monitor a set of parameters selected from state of charge (SoC), state of health (SoH), temperature, and voltage;
c. a central controller interconnected to said ESDs and sensors to process data received from ESD Management Units (EMUs), sensors, and other vehicle systems, said central controller employing an optimization technique to optimize power distribution among said ESDs;
d. a communication device wirelessly connected to the central controller to employ state-of-the-art bidirectional communication protocols, including high-speed wired and wireless technologies selected from Controller Area Network (CAN), Ethernet, or Bluetooth, for seamless communication between the CPU and each battery pack;
e. a user interface integrated into a vehicle's dashboard or infotainment system through the communication device, allowing driver to monitor and configure ESD management settings, wherein said user interface provides real-time data visualization and configuration options;
f. an onboard charging unit, an electro-mechanical/electronic unit configured to charge said ESDs intelligently based on system requirements;
g. one or more voltage balancing circuits featuring advanced passive or active balancing techniques, intelligently controlled by the CPU to address voltage differentials among individual battery cells within each pack; and
h. a safety mechanism incorporating the latest advancements in sensing and actuation technologies to detect and respond to abnormal conditions promptly, including overvoltage, overcurrent, or overheating, ensuring the swift and secure isolation of affected battery packs.

2. The system as claimed in claim 1, wherein said ESD Management Unit (EMU) associated with each battery pack, said EMU is configured to communicate with said central controller, collect real-time data from said ESDs, and transmit said data to said central controller.

3. The system as claimed in claim 1, wherein said central controller employs an optimization technique to optimize power distribution among said battery packs, wherein said optimization technique is selected from a dynamic load balancing technique for optimizing power distribution among said ESDs based on their state of charge, health, and other parameters, a predictive power management technique for forecasting energy demand and adjusting distribution of power accordingly; an adaptive charging technique for dynamically adjusting charging rates of individual ESDs based on real-time conditions; a fault tolerance technique for identifying and isolating malfunctioning ESDs to ensure reliability and safety and a machine learning-based optimization technique for continuously learning and adapting to driving patterns, environmental conditions, and ESD characteristics to enhance long-term performance.

4. The system as claimed in claim 1, further comprises:
a predictive maintenance unit utilizing machine learning algorithms to anticipate potential battery issues based on historical data and initiate preventive measures;
an augmented thermal management unit that employs advanced sensor technologies, strategically placed heat sinks, and dynamically controlled cooling fans to maintain optimal operating temperatures for each battery pack under diverse and challenging conditions; and
a telematics module for seamless remote monitoring and control of electric vehicle battery packs, providing enhanced connectivity and compatibility with external entities such as advanced fleet management systems or evolving charging infrastructures.

5. The system as claimed in claim 1, wherein said central controller intelligently and dynamically splits said onboard ESDs into two groups in real-time, wherein a first group of ESDs provides energy to drive said vehicle and other accumulating energy for later use.

6. The system as claimed in claim 5, wherein a second group of ESDs receives stored energy from said onboard charging unit, enhancing overall operational performance of said electric vehicle.

7. The system as claimed in claims 5 and 6, wherein selection of said first and second ESDs for driving or charging is dynamically performed by said EMU, incorporating inherent intelligence for optimal energy management.

8. The system as claimed in claim 1, wherein the power distribution optimization, comprises:
a preprocessing module connected to said data acquisition module to preprocess real-time data from ESD Management Units (EMUs)data to eliminate noise and normalize said data to a common scale;
a state evaluation module connected to said preprocessing module to evaluate current state of each ESD based on received data, assessing overall health and performance of said ESDs;
an energy demand forecasting module connected to said state evaluation module to utilize historical data and machine learning techniques to forecast energy demand for upcoming driving cycle, and adjust forecasts based on real-time factors;
an optimization module connected to said energy demand forecasting module to employ optimization techniques to determine optimal power distribution among said ESDs;
a dynamic adjustment module connected to said optimization module to dynamically adjust power distribution based on changing conditions during the driving cycle, continuously monitor ESD parameters, and adjust distribution in response to changes in energy demand or ESD performance;
a fault tolerance and mitigation module connected to said dynamic adjustment module to implement fault tolerance mechanisms to identify and isolate malfunctioning ESDs, and mitigate impact of faults by redistributing power among healthy ESDs;
a user interface update module connected to said fault tolerance and mitigation module to update said user interface with real-time information on ESD status, power distribution, and system performance, and provide alerts or recommendations to said driver if needed; and
an adaptive learning module connected to said user interface update module to implement adaptive learning mechanisms to continuously improve optimization techniques based on historical performance data and incorporate machine learning models to adapt to evolving driving patterns and environmental conditions.

9. A method for managing energy in an electric vehicle, the method comprises:
a. integrating a plurality of energy storage devices (ESDs) into an electric vehicle;
b. monitoring a set of parameters selected from state of charge (SoC), state of health (SoH), temperature, and voltage by strategically placing sensors within each ESD;
c. collecting and transmitting real-time data from said ESD to a central controller by equipping each ESD with an ESD Management Unit (EMU) that communicates with said central controller;
d. processing data received from said EMUs, sensors, and other vehicle systems with said central controller, using optimization techniques to optimize power distribution among said ESDs;
e. monitoring and configuring ESD management settings by providing a User Interface for a driver; and
f. employing an On-board Charging Unit to intelligently and dynamically split said ESDs into two groups in real-time, where a first group provides energy to drive said vehicle and a second group accumulates energy for later use, with said selection of ESDs for driving or charging purposes dynamically determined by said EMU, thereby enhancing overall operational performance of said electric vehicle.

10. The method as claimed in claim 9, wherein said power distribution optimization comprises the steps of:
receiving real-time data from ESD Management Units (EMUs), including SoC, SoH, temperature, and voltage for each ESD, and collecting data from sensors monitoring relevant parameters in said vehicle and its surroundings;
preprocessing acquired data to eliminate noise and ensure accuracy, and normalizing said data to a common scale;
evaluating current state of each ESD based on received data, assessing an overall health and performance of said ESDs;
forecasting energy demand for an upcoming driving cycle, and adjusting forecasts based on real-time factors by utilizing historical data and machine learning techniques;
determining said optimal power distribution among said ESDs by employing optimization techniques;
adjusting power distribution based on changing conditions during driving cycle, continuously monitoring ESD parameters, and adjusting distribution in response to changes in energy demand or ESD performance;
identifying and isolating malfunctioning ESDs, and mitigating impact of faults by redistributing power among healthy ESDs upon implementing fault tolerance mechanisms;
updating said user interface with real-time information on ESD status, power distribution, and system performance, and providing alerts or recommendations to said driver if needed; and
implementing adaptive learning mechanisms to continuously improve optimization techniques based on historical performance data and incorporating machine learning models to adapt to evolving driving patterns and environmental conditions.