Self-Calibrating Battery Management System for Aging Control
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Solution Overview
Problem
Existing battery management systems face challenges in accurately diagnosing and controlling battery aging due to rapid advancements in energy density and cell chemistry, leading to reduced safety margins and increased complexity in managing voltage, temperature, and charge/discharge cycles, especially in high-performance applications where empirical data is scarce.
Innovation Solution
A self-calibrating battery management system that employs a numerical battery model comprising parametrized electric, thermal, and aging models to control state of charge, current, voltage, and power, using a closed-loop control system to adapt settings based on stress parameters and update parameters dynamically, reducing the need for extensive a priori characterization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If batteries are designed with higher energy density to increase power and energy output, then productivity and performance are improved, but safety margins are reduced and the risk of thermal runaway increases
Solution Approach 1:
The system performs preliminary thermal runaway detection by continuously monitoring battery parameters and comparing them against predicted values from a thermal model before actual thermal runaway occurs. This early detection enables preventive actions to be taken, resolving the contradiction by allowing higher energy density batteries to operate safely through early warning systems.
Solution Approach 2:
The system implements continuous feedback by monitoring battery temperature, voltage, and current, comparing actual measurements with model predictions, and adjusting control parameters in real-time. This feedback mechanism allows high-energy-density batteries to maintain safety margins through dynamic adjustment, resolving the contradiction between productivity and reliability.
2Measurement precision
If extensive a priori testing is performed to characterize battery aging behavior, then measurement precision and reliability are improved, but the time required for battery system development increases significantly
Solution Approach 1:
The system employs self-service by using the battery's own operational data during normal use to continuously update and refine the aging model parameters. This eliminates the need for extensive separate characterization testing, as the battery characterizes itself during operation, resolving the contradiction between measurement precision and development time.
Solution Approach 2:
The system performs preliminary characterization by establishing initial aging models with default parameters that provide adequate measurement precision from the start, without requiring extensive a priori testing. The model is then refined over time using operational data, resolving the contradiction by providing immediate usability with sufficient accuracy.
3Reliability
If a fixed and reduced operational range is used to ensure safe operation from beginning to end of life, then reliability is improved, but the battery size increases and competitiveness decreases
Solution Approach 1:
The system implements dynamic operational ranges that adapt in real-time based on the battery's actual state, age, and environmental conditions, rather than using fixed reduced ranges. This allows the battery to operate at optimal capacity throughout its life while maintaining safety, resolving the contradiction between reliability and battery size by eliminating the need for conservative fixed margins.
Solution Approach 2:
The system changes operational parameters dynamically by adjusting voltage, current, and temperature limits based on real-time monitoring and model predictions. This allows the battery to safely operate across a wider range of conditions without increasing physical size, resolving the contradiction between reliability and competitiveness.
4Productivity
If new cell types and chemistries are developed faster to meet market demands, then productivity is improved, but the availability of empirical data for complete characterization decreases
Solution Approach 1:
The system performs self-characterization by continuously collecting and analyzing operational data from new cell types during normal use, building empirical data sets without requiring extensive separate testing. This resolves the contradiction by allowing rapid development of new chemistries while simultaneously generating the necessary characterization data through operational self-monitoring.
Solution Approach 2:
The system implements continuous feedback loops that collect operational data and use it to refine model parameters for new cell types in real-time. This feedback mechanism enables complete characterization of new chemistries to be achieved through normal operation rather than extensive pre-testing, resolving the contradiction between development speed and data availability.
Data Source
AI summary
A battery management system for a rechargeable battery is disclosed which includes a control system configured to control, a numerical battery model, including a parametrized electric model; a parametrized thermal model; an aging model configured to provide stress parameters indicative of an instantaneous consumption of an expected lifetime of the battery in dependence on an internal temperature of the battery, and one or more of momentary state of charge, current, voltage and power delivered; updated electric parameters and/or updated thermal parameters based on a chronological sequence of internal temperature as obtained from the parametrized thermal model; a control system settings update unit configured to adapt controller settings based on stress parameters.