Charging method and device of electric locomotive battery

By using Kalman filtering algorithm and linear compensation model in the motor vehicle battery system, the battery health status and life are evaluated in real time, faults are identified through the abnormal detection module, and charging strategies are dynamically adjusted, the battery capacity attenuation and internal resistance are solved, which extends the battery life and improves the system reliability.

CN119742479AActive Publication Date: 2025-04-01SHENZHEN LIDINGPENG INTELLIGENT TECH CO LTD
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Patent Information

Application Number
CN202510261178.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-06
Publication Date
2025-04-01
Estimated Expiration
2045-03-06

AI Technical Summary

Technical Problem

The existing motor vehicle battery system is prone to capacity decay and internal resistance increase during high-frequency charging and discharging, resulting in a decrease in health status and a shortened service life. The existing charging technology is difficult to dynamically adjust the charging strategy according to the real-time status of the battery, and it is impossible to effectively identify various causes and effects of faults.

Method used

By obtaining battery operation parameters, combining Kalman filtering algorithm and linear compensation model for high-precision filtering and calibration, the battery health status and remaining service life are evaluated in real time, the optimal charging strategy is generated, and a variety of fault types are identified through the abnormality detection module, and the charging parameters are dynamically adjusted to ensure the safe operation of the battery.

Benefits of technology

Accurate evaluation of the health status and life of the battery and dynamic charging control are achieved, extending the battery life and improving the overall reliability and safety of the track power battery system.

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Abstract

The invention provides an electric locomotive battery charging method and device, and relates to the technical field of battery charging, and the method comprises the steps: carrying out the data cleaning and feature extraction based on the preliminarily processed battery operation parameters, calculating the battery health state based on the obtained health state, obtaining the health state parameters, and storing the health state parameters; and calculating the remaining service life based on the obtained life prediction result to obtain a life prediction parameter, carrying out anomaly detection and fault identification based on the obtained health state parameter and life prediction parameter, and carrying out report generation based on the obtained health state parameter and life prediction parameter to obtain first report data. The high-precision sensor is combined with a filtering and data calibration algorithm, so that high-frequency noise and system errors in battery operation parameters are effectively eliminated, the calculation precision of health state parameters and life prediction parameters is remarkably improved, and the reliability under various complex operation conditions is ensured.
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