Battery End-of-Life Estimation Using SOH Trend Feedback
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Solution Overview
Problem
There is a need for an accurate and effective method to estimate the end of life of rechargeable batteries in electric vehicles, as the lifespan varies based on usage and different vehicles use different types of batteries, leading to potential premature replacement and stock issues.
Innovation Solution
A system that includes sensors to measure the state of health (SOH) of the battery, a processing unit to calculate a new replace-by date based on recent and historical SOH measurements, and communication for preordering replacement batteries, using curve fitting algorithms to extrapolate the battery's remaining life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If a predetermined replace-by date is set by the manufacturer, then users can plan battery replacement in advance, but users may replace batteries prematurely before they actually need replacement
Solution Approach 1:
The system changes the parameter from a fixed predetermined date to a dynamic estimate based on measured state of health (SOH) parameters. The processing unit continuously monitors battery SOH and calculates replace-by dates based on actual degradation rates, allowing the replacement timing to adapt to individual usage patterns and battery conditions.
Solution Approach 2:
The system implements feedback by continuously measuring the battery's state of health and using this information to update and refine the replace-by date estimate. The processing unit compares actual SOH measurements with the predicted degradation model, enabling accurate tracking of battery aging and dynamic adjustment of the replacement schedule.
2Reliability
If users wait until the predetermined replace-by date, then they ensure battery functionality, but they may face manufacturer stock issues and replacement delays
Solution Approach 1:
The system performs preliminary action by calculating and notifying users of the replace-by date in advance based on actual battery degradation trends. This allows users to plan and coordinate battery replacement with the manufacturer well before the estimated end-of-life date, ensuring compatibility and availability of replacement batteries while avoiding premature replacement.
3Adaptability or versatility
If different vehicle types use different battery types, then each vehicle gets optimized performance, but manufacturers may be out of stock of compatible replacement batteries
Solution Approach 1:
The system uses the processing unit and communication system as intermediaries between the battery, vehicle, and manufacturer. The processing unit identifies the specific battery type and vehicle compatibility requirements, then communicates this information to the manufacturer in advance, coordinating replacement logistics and ensuring the correct battery model is available before the user needs it.
Data Source
AI summary
Methods and systems of estimating an end of life of a rechargeable energy storage device in an energy storage system is disclosed. The system includes at least a motor, the energy storage device associated with the motor, a processing unit associated with the energy storage device, and at least one sensor operatively coupled with the processing unit and the energy storage device. The method includes measuring a most recent state of health (SOH) of the energy storage device after the system is started, storing the most recent SOH with at least one previously measured SOH, calculating a new replace-by date of the energy storage device based on the most recent SOH and the at least one previously measured SOH, and replacing a previously calculated old replace-by date with the new replace-by date, the new replace-by date being the same as or shorter than the old replace-by date.