RC Battery Current Limit Estimation Under Polarization Effects
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Solution Overview
Problem
Existing Battery Management Systems (BMS) in hybrid electric vehicles and electric vehicles inaccurately calculate battery current limits due to oversimplification and neglect of important parameters like battery polarization, especially in aged batteries and low-temperature conditions.
Innovation Solution
A method using an RC equivalent circuit model to estimate Li-ion battery current limits by considering mechanical, charge conservation, kinetic, and dynamic limitations, incorporating state of charge, temperature, and state of health, and employing methods like Hybrid Pulse Power Characterization and State of Charge Limitation to determine discharge and charge current limits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If conventional simplified methods are used to calculate battery current limits, then the calculation process is simple and fast, but the accuracy of current limit estimation deteriorates, especially in aged batteries and low-temperature conditions
Solution Approach 1:
The patent changes the parameters considered in current limit calculation from simplified conventional parameters to a comprehensive set including battery polarization level, state of charge, temperature, and state of health. The RC model dynamically adjusts these parameters to accurately reflect actual battery conditions, resolving the contradiction between calculation simplicity and accuracy by automating complex parameter tracking.
Solution Approach 2:
The patent introduces an RC equivalent circuit model as an intermediary between the battery and the BMS calculation system. This model acts as a mediator that captures complex battery behaviors (polarization, temperature effects, aging) and translates them into usable current limit estimates, maintaining accuracy while managing computational complexity through model-based estimation.
2Ease of manufacture
If manufacturer-reported current limits based on fully rested initial conditions are used, then the current limits are easily obtained, but they become overestimations when batteries operate from non-rested conditions
Solution Approach 1:
The patent transitions from static manufacturer-reported current limits to dynamic current limit estimation that adapts to real-time battery conditions. The RC model continuously updates polarization levels and adjusts current limits based on actual operating states (charge/discharge history, temperature, SOC), ensuring reliability while maintaining ease of data acquisition through standard BMS measurements.
Solution Approach 2:
The patent implements feedback mechanisms where the RC model continuously monitors battery voltage, current, and temperature measurements, updates the polarization state, and adjusts current limit estimates accordingly. This closed-loop approach ensures that current limits reflect actual battery conditions rather than relying on static manufacturer data, resolving the reliability issue while using readily available sensor data.
3Device complexity
If battery polarization effects are ignored in current limit calculation, then the calculation method remains simple, but the accuracy deteriorates in low and high SOC and low temperature conditions
Solution Approach 1:
The patent introduces an RC equivalent circuit model as an intermediary that specifically captures polarization effects. The model uses resistors and capacitors to represent different time constants of battery polarization, allowing accurate estimation of polarization voltage drops without requiring complex calculations. This resolves the contradiction by isolating polarization modeling into a dedicated subsystem.
Solution Approach 2:
The patent segments the battery model into distinct RC circuits representing different polarization time constants (fast and slow polarization). Each RC branch independently models specific polarization effects, allowing the system to accurately capture polarization behavior across different time scales and operating conditions while keeping individual calculations manageable and modular.
Data Source
AI summary
A method of estimating a battery current limit for operation of a battery cell over the course of a specified prediction time. The method includes generating a plurality of current limit estimations by means of a plurality of current limit estimation sub-methods, wherein at least one current limit estimation sub-method generates its current limit estimation based on an RC equivalent circuit model of the battery cell, and determining the charge current limit by finding the lowest magnitude current limit estimation in the plurality of current limit estimations. At least one parameter of the RC equivalent circuit model is set based on the specified prediction time and at least one variable from the set of: a state of charge (SOC) of the battery cell, a temperature of the battery cell, a state of health (SOH) of the battery cell, a capacity of the battery cell, and a current of the battery cell.