Kalman Filter Mathematical Algorithm for Estimating the State of Charge of Automotive Batteries

AUTO ELECTRIC PARTS ›› 2026, Vol. 1 ›› Issue (2) : 23-25.

New Energy

Zhao Qingqing

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Abstract

In the context of global energy structure transformation and the upgrading of environmental protection demands, electric vehicles are leading a profound transformation in the automotive industry. As a core component, the performance of the power battery directly determines the vehicle's range, safety performance, and operational reliability. The State of Charge (SOC) is a key parameter that indicates the remaining battery capacity and is of great significance for optimizing energy allocation strategies, preventing overcharging and overdischarging of the battery, and extending the battery's service life. This paper focuses on the issue of SOC estimation for power batteries, systematically analyzing its theoretical basis and technical bottlenecks, elaborating on the modeling application of Kalman Filter theory and the key points of algorithm performance evaluation, providing theoretical references and technical support for engineering practice.

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automotive power batteries / SOC estimation / Kalman Filter / algorithm optimization

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Zhao Qingqing. Kalman Filter Mathematical Algorithm for Estimating the State of Charge of Automotive Batteries[J]. AUTO ELECTRIC PARTS. 2026, 1(2): 23-25