Abstract
Energy crisis and environmental pollution stimulate the rapid development of new energy electric vehicles. The state of charge(SOC) is a key parameter of power battery in application, so the accurate estimation is extremely important. Factors affecting the battery SOC are many and complicated, scholars have proposed many methods to estimate SOC, but still does not solve the accuracy and practicability of the demand very well. In recent years, intelligent scheme has been successfully applied, but the traditional scheme only consider a single mode of learning, when conditions change, estimation error of SOC is fluctuating. This paper adopts the intelligent scheme based on BP neural network to model and predict power battery SOC. At the same time, genetic algorithm is used to optimize the network parameters in order to improve the predicting accuracy.
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