Battery State of Energy Estimation Using SOC Discrepancy Charts
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Solution Overview
Problem
Current state-of-charge estimators for batteries are limited in their applicability, particularly as they do not account for battery aging and are complex to implement, with few effective methods available for estimating the state of energy (SOE) relevant to the available energy in the battery.
Innovation Solution
A method that estimates the state of energy (SOE) by determining the discrepancy between the state of charge (SOC) and SOE, using charts produced experimentally or simulated, considering parameters like power, state of health, and temperature, to compute the available energy in the battery, which is simpler to implement than existing neural network-based solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If neural network-based estimators are used to estimate state of energy, then estimation accuracy is improved, but implementation complexity increases
Solution Approach 1:
The estimation process is divided into two independent stages: first estimating state of charge (SOC) using conventional methods, then calculating state of energy (SOE) from SOC using pre-determined discrepancy charts. This segmentation avoids the need for complex neural networks while maintaining estimation accuracy.
Solution Approach 2:
Discrepancy charts showing the relationship between SOC and SOE are pre-determined through experimentation or simulation and stored for later use. This preliminary action eliminates the need for real-time complex calculations during actual battery operation, simplifying implementation while preserving accuracy.
2Ease of manufacture
If conventional state of charge estimators are used, then implementation is simple, but they do not account for battery aging and provide limited applicability
Solution Approach 1:
Discrepancy charts serve as an intermediary element that bridges simple SOC estimation with accurate SOE calculation while accounting for battery aging. These charts encapsulate aging effects and are applied to conventional SOC estimators, maintaining implementation simplicity while enhancing adaptability across the battery lifecycle.
3Measurement precision
If integration of voltage curve over SOC interval is used to determine state of energy, then estimation is provided, but the method is complex and limited to specific cases
Solution Approach 1:
Instead of performing complex real-time voltage curve integration, the patent uses pre-computed discrepancy charts that copy the essential relationship between SOC and SOE. This copying approach maintains estimation accuracy while dramatically reducing computational complexity and broadening applicability beyond specific cases.
Data Source
AI summary
A method for estimating a state of energy of a battery, comprising the steps of estimating a state of charge of the battery, determining a discrepancy between the state of charge and the state of energy as a function of the state of charge, computing the state of energy as a function of the estimated state of charge and of the determined discrepancy. Also a battery including apparatus configured to implement the method is provided.