Battery ECU Degradation Estimation After Controller Replacement
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Solution Overview
Problem
Existing battery degradation estimation systems face memory overflow issues when the control device is replaced, as frequency data is not present in the replaced control device's memory, leading to inaccurate degradation estimation.
Innovation Solution
A battery system configuration where a first control device estimates degradation using frequency data and a degradation coefficient that increases with temperature, and a second control device stores the estimated degradation. Upon replacement, the first control device acquires the degradation from the second and creates new frequency data in high-temperature regions with higher degradation rates, minimizing memory overflow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency data is stored in the control device memory for long-term battery degradation estimation, then degradation estimation accuracy is improved, but memory overflow occurs after device replacement
Solution Approach 1:
The patent extracts only the necessary degradation information from the frequency data and stores it separately in a degradation amount storage unit. This separates the large-volume raw frequency data from the essential degradation metrics, allowing accurate degradation estimation without storing complete historical frequency data, thus preventing memory overflow while maintaining estimation precision
Solution Approach 2:
The patent transforms the raw frequency data into degradation amounts through calculation using Arrhenius law and degradation coefficients. By changing the parameter representation from raw temperature frequency history to calculated degradation amounts, the system achieves accurate long-term degradation tracking with minimal stored data, resolving the contradiction between estimation accuracy and memory capacity
2Reliability
If complete frequency data is transferred from old control device to new control device upon replacement, then degradation estimation continuity is improved, but data transfer complexity and memory overflow risk increase
Solution Approach 1:
Instead of copying complete frequency data, the system copies only the calculated degradation amounts from the old control device to the new one. This simplified copying process maintains degradation estimation continuity while dramatically reducing data transfer complexity and eliminating memory overflow risks associated with transferring complete historical frequency data
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Accurate battery degradation estimation is maintained post-replacement by creating new frequency data in high-temperature regions, reducing the likelihood of memory overflow and improving estimation accuracy.
Implementation Method 1
a temperature sensor configured to detect a battery temperature that is a temperature of the battery
Implementation Method 2
there are cases where the degree of degradation (amount of damage and amount of degradation) of a battery is estimated according to Arrhenius law using the frequency distribution (history) of the battery temperature
Data Source
AI summary
The battery ECU updates the frequency data of the area using the temperature TB and SOC of the battery as parameters, and estimates the degradation degree (degradation amount) from the frequency data and the degradation coefficient that increases as the temperature TB increases. The degradation degree is stored in the control ECU. When the battery ECU is replaced, the battery ECU acquires the degradation level from the control ECU and creates a new frequency based on the degradation level. The new frequency data is created as frequency data F of an area having a high temperature TB and a large SOC, and the other area is set to a NULL.