Battery Model Adaptation for Aging-Accurate Power Prediction
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Solution Overview
Problem
Electrical energy storage units in vehicles experience aging effects, leading to changes in internal resistance, making it difficult to accurately predict available power and determine when replacement is necessary, as initial resistance values become outdated and vary between units.
Innovation Solution
A procedure that checks predefined conditions such as state of charge, temperature, and age to adapt a mathematical model of the energy storage unit, ensuring increased accuracy and robustness by updating parameter values and filtering voltage measurements to improve model accuracy and ignore aging effects early in the life cycle.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If initial resistance values are used for prediction, then device complexity is reduced, but measurement precision deteriorates due to aging effects and unit variations
Solution Approach 1:
The system performs preliminary characterization of each energy storage unit during manufacturing or initial operation to determine unit-specific parameters (R0, R1, C1, etc.). These parameters are stored and used to initialize the mathematical model before normal operation begins, allowing the model to be pre-adapted to each unit's characteristics without requiring complex real-time adjustments.
Solution Approach 2:
The system continuously compares the mathematical model's predicted voltage output with actual measured voltage from the energy storage unit. When deviations exceed a threshold, the system triggers parameter adaptation by solving the differential equation with measured current and voltage data to update the model parameters, ensuring ongoing accuracy despite aging effects.
2Measurement precision
If mathematical model parameters are continuously updated, then measurement precision improves, but device complexity increases due to additional calculations and data processing
Solution Approach 1:
Instead of continuously updating all model parameters at every time step, the system performs parameter adaptation only partially - specifically when voltage deviations exceed a predefined threshold. This selective updating approach maintains sufficient accuracy while significantly reducing computational burden compared to continuous full-parameter re-identification.
Solution Approach 2:
The system changes the mathematical model's parameters (R0, R1, C1, R2, C2) from fixed initial values to adaptive values that evolve over time based on measured operational data. This allows the model to track aging effects and unit variations without requiring complex structural modifications to the underlying differential equation framework.
3Measurement precision
If unit-specific parameter determination is implemented, then measurement precision improves for individual units, but loss of time increases due to additional characterization steps
Solution Approach 1:
Unit-specific parameter characterization is performed as a preliminary step during manufacturing or initial commissioning, before the energy storage unit enters normal operational service. This front-loads the time investment, allowing accurate unit-specific modeling without impacting the unit's operational availability or service time.
Solution Approach 2:
The system uses the energy storage unit's own operational data (measured voltage and current during normal operation) to automatically adapt and refine its parameters. This self-characterization approach eliminates the need for separate external testing or characterization procedures, performing the identification process using the unit's normal operational cycles.
Data Source
AI summary
An apparatus, computer program, storage medium and electrical energy storage system for operating an electrical energy storage unit. The procedure includes ascertaining at least one predefined first condition being checked which represents a use of the electrical energy storage unit and/or an accuracy of a mathematical model of the electrical energy storage unit. If the predefined first condition is satisfied, at least one value of a parameter of the mathematical model is ascertained and subsequently this parameter value is changed in the mathematical model. The electrical energy storage unit is subsequently operated with the changed mathematical model.