Battery SOC Estimation via State-Segmented Equivalent Models
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Solution Overview
Problem
Conventional methods for estimating the state of charge (SOC) of battery cells in vehicles are computationally inefficient, particularly when batteries frequently transition between operational states, which is a challenge for automotive implementations.
Innovation Solution
A method involving the formation of multiple battery cell equivalent models for different operational states, where an output parameter from a previous model is used as an input for a subsequent model to enhance computational efficiency and reduce errors, utilizing RC-based circuit models and hysteresis to manage state transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple battery cell equivalent models are used for different operational states, then measurement precision of SOC estimation is improved, but device complexity increases
Solution Approach 1:
The battery operational states are segmented into distinct categories (charging, discharging, relaxation) with dedicated equivalent models for each state. This segmentation allows each model to be optimized for its specific operational context, improving measurement precision while managing complexity through targeted model design rather than a single complex universal model.
Solution Approach 2:
The patent changes parameters (operational state conditions) to select appropriate equivalent models. By monitoring parameters such as current direction and magnitude, the system transitions between different equivalent models, maintaining high SOC estimation accuracy across varying operational conditions without requiring one overly complex model to handle all scenarios.
2Productivity
If output parameter from previous model is provided as input parameter for subsequent model during state transitions, then productivity of SOC calculation is improved, but reliability may worsen due to error propagation
Solution Approach 1:
The patent applies preliminary action by using output parameters from previously applied equivalent models as initial conditions for subsequent models during state transitions. This pre-positioning of data eliminates computational delays and ensures continuous SOC estimation without interruption during transitions between charging, discharging, and relaxation states, thereby improving productivity.
3Device complexity
If conventional SOC calculation methods are used, then device complexity is reduced, but loss of time increases due to computational inefficiency during state transitions
Solution Approach 1:
The patent introduces dynamics by adapting the equivalent model selection based on real-time operational state transitions. Instead of a static single-model approach, the system dynamically switches between charging, discharging, and relaxation equivalent models based on current operational conditions, reducing computational time during transitions while maintaining manageable system complexity through clear state-based categorization.
Data Source
AI summary
The present disclosure relates to a method of estimating a charge state for a battery cell, specifically taking into account different operational states (402, 404, 406, 408) of the battery cell. The present disclosure also relates to a battery management arrangement (200) and to a corresponding computer program product.