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Structure designing of BP neural network in the application of reference velocity estimation

BP neural network (BPNN) is used to estimate vehicle velocity when car brakes and ABS functions. Based on Fuzzy C-Means (FCM) clustering algorithm, a new empirical formula of hidden-layer nodes is proposed. Adding delays to the input-layer of BPNN for expanding the input sample space can improve estimated accuracy greatly. The appropriate distributed delays selected can reduce the redundancy of the network structure, and improve the mapping relationships of the inputs and outputs. Velocity estimation is simulated on the condition of high adhesion-coefficient road, and the results show that the absolute error is no more than 1 km/h and the relative error is no more than 0.4%.