论文信息 - Estimating the State of Charge for Ni-MH Battery in HEV by RBF Neural Network

Estimating the State of Charge for Ni-MH Battery in HEV by RBF Neural Network

Forecasting of the state of charge (SOC) of Ni-MH battery is the most important task for battery management system of hybrid electric vehicle (HEV). On the basis of analyzing charging and discharging characteristics of Ni-MH battery and using the advantages of radial basis function (RBF) neural network, model for estimating the state of charge for Ni-MH battery was established with the piecewise modeling idea. The model was tested with data which was from battery experiments. Results show that the operation speed and estimation accuracy of forecasting model can meet the demands in practice and the model has certain value of application.

Hongyu Guo | Jiuchun Jiang | Zhanguo Wang

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