Tire Load Measurement Method Based on PSO-BP Neural Network
The tire load measurement method based on particle swarm optimization(PSO)algorithm-BP neural network was studied.The collected tire condition information and extracted acceleration features were input into the BP neural network to regressively predict the tire load.The weight and threshold of BP neural network were optimized by PSO algorithm,and the relationship between tire state information and tire load was obtained.The results showed that the prediction error for tire load using the PSO-BP neural network was 1.865 6％and the prediction accuracy of PSO-BP neural network was higher.Under changing working conditions,the prediction error was 2.496％.
tire loadtire status informationacceleration characteristicPSO algorithmBP neural network
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