Intelligent EV Battery Charging Control Logic
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Solution Overview
Problem
Rechargeable traction battery packs in electric vehicles face premature degradation due to large state of charge (SOC) swings and extreme operating temperatures, leading to reduced operational life, as existing charging systems lack effective management of charging behaviors to prevent overcharging and undercharging.
Innovation Solution
A closed-loop feedback control system that monitors and analyzes SOC and temperature data to predict potential degradation, providing user feedback and automating charging operations to limit SOC and temperature excursions, thereby extending battery life by restricting charging outside specified thresholds and optimizing charging behaviors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If charging is performed without management control, then charging speed and convenience are improved, but battery degradation accelerates due to large SOC swings and extreme temperatures
Solution Approach 1:
The system continuously monitors battery SOC and temperature, comparing real-time data against predefined thresholds. When thresholds are exceeded, the system automatically adjusts charging parameters or terminates charging, creating a closed-loop feedback mechanism that prevents degradation while maintaining efficient charging operation
Solution Approach 2:
The system establishes predefined SOC and temperature thresholds before charging begins. By setting these boundary conditions in advance, the system proactively prevents harmful charging conditions before they occur, rather than reacting after damage has been done
2Reliability
If charging is restricted to optimal SOC and temperature ranges, then battery life is extended, but charging flexibility and user autonomy are reduced
Solution Approach 1:
The system dynamically adjusts charging parameters based on real-time battery conditions. When SOC and temperature are within optimal ranges, charging proceeds at maximum speed. When thresholds are approached, the system automatically modifies charging rate or terminates charging, creating a dynamic adaptation that balances battery protection with charging efficiency
Solution Approach 2:
The battery management system autonomously monitors its own state and makes charging decisions without requiring user intervention. The system self-regulates charging parameters based on predefined thresholds, eliminating the need for users to manually manage charging flexibility while still protecting battery life
3Reliability
If monitoring and control systems are implemented, then battery degradation is prevented, but system complexity increases
Solution Approach 1:
The system focuses monitoring and control on the two most critical degradation parameters: SOC and temperature. By concentrating resources on these key parameters rather than attempting to control all possible variables, the system achieves effective battery protection with minimal complexity
Solution Approach 2:
The control logic is segmented into simple, discrete threshold checks for SOC and temperature. Rather than implementing a complex continuous control algorithm, the system divides the control space into distinct regions (below threshold, within threshold, above threshold) with simple corresponding actions, reducing overall system complexity
Data Source
AI summary
Presented are control systems for operating rechargeable electrochemical devices, methods for making/using such systems, and vehicles with intelligent battery charging and charging behavior feedback capabilities. A method of operating a rechargeable battery includes an electronic controller receiving battery data from a battery sensing device indicative of a battery state of charge (SOC). Using this battery data, the controller determines a number of low SOC excursions at which the battery SOC is below a predefined low SOC threshold and a number of high SOC excursions at which the battery SOC exceeds a predefined high SOC threshold. The controller then determines if the number of low SOC excursions exceeds a predefined maximum allowable low excursions and/or the number of high SOC excursions exceeds a predefined maximum allowable high excursions. If so, the controller responsively commands a resident subsystem to execute a control operation that mitigates degradation of the rechargeable battery.