Battery State of Charge Estimation Using Cell Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for estimating the state of charge of electric batteries are inaccurate due to cell imbalance, where cells within a battery have different states of charge, leading to unreliable range estimates for electric vehicles, potentially causing drivers to run out of energy or face dangerous situations.
Innovation Solution
A method that determines the state of charge of each cell and calculates the battery's state of charge as the ratio of the least charged cell to the range defined by the difference between the most and least charged cells, using a Kalman filter-based state observer that accounts for temperature and lifetime variations, and integrates current to estimate charge accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the state of charge is estimated based on measurements of the battery as a whole (average of cells), then the measurement process is simple, but the measurement precision deteriorates due to cell imbalance
Solution Approach 1:
The patent segments the battery into individual cells and estimates the state of charge for each cell separately using a Kalman filter, rather than estimating a single average state of charge for the entire battery. This segmentation allows the system to account for cell-to-cell variations and imbalances, significantly improving measurement precision while the modular Kalman filter implementation keeps computational complexity manageable.
2Reliability
If the battery range is determined by the most charged and least charged cells, then the reliability of range information improves, but the loss of information increases because the average state of charge no longer represents the battery capacity
Solution Approach 1:
The patent uses a Kalman filter that continuously processes feedback from individual cell voltage and current measurements to estimate each cell's state of charge. This feedback mechanism allows the system to dynamically track the state of charge of each cell and determine the battery's usable range based on the most charged and least charged cells, while maintaining accurate information about the overall battery state through the filter's internal model.
3Measurement precision
If individual cell states of charge are tracked separately, then the measurement precision of individual cells improves, but the device complexity increases due to additional calculations and data processing
Solution Approach 1:
The patent implements a universal Kalman filter algorithm that serves multiple functions simultaneously: it estimates the state of charge for each individual cell, tracks cell-to-cell imbalances, determines the battery's usable range, and provides continuous state estimation as the battery charges and discharges. This multi-functional approach improves measurement precision while avoiding the need for separate complex systems for each function.
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
The invention relates to a method of estimating the state of charge (SOCbatt_k) of an electric battery comprising a plurality of electric accumulators called cells. According to the invention, it comprises the following steps: a) the state of charge (SOCcell_est_i) of each cell of the battery is determined, b) a range of use of the battery equal to a maximum predetermined value of the state of charge of a cell minus the deviation between the state of charge (SOCcell_max_k) of the most charged cell and the state of charge of the least charged cell (SOCcell_min_k) which are determined in step a) is determined, c) the state of charge of the battery (SOC_batt_k) is determined as being equal to the ratio between the state of charge of the least charged cell (SOCcell_min_k) determined in step a) and said range of use of the battery determined in step b).