Quantitative Model of Vehicle Pedal Movement Based on Triboelectric Nanogenerators

doi:10.3901/JME.2022.17.215

Abstract

Abstract: Aiming at the problem of complex structure, dependence on complex materials and external power supply of vehicle pedal angle sensor. A quantization model of pedal movement based on the fan-shaped sector-single electrode sliding mode triboelectric nanogenerator (S-SETENG) is proposed. First, on the basis of the single electrode sliding mode triboelectric nanogenerator (SETENG), according to the potential law between the contact area and the open circuit voltage value, the S-SETENG that can obtain pedal movement information is developed. Secondly, through the simulated driving experiment, the pedal movement data in the natural driving state is obtained, including the pedal angle data output by the driving simulator and the voltage data output by S-SETENG. Then, using S-SETENG voltage data and vehicle pedal angle data to complete the training of pedal movement quantification model. Finally, according to the results of the prediction models on the test set, the acceleration pedal movement quantization model based on gate recurrent unit (GRU) and the brake pedal movement quantization model based on long-short term memory (LSTM) perform best, and the value of R square(R²) exceeds 0.94, which proves the accuracy and feasibility of this method. This not only presents a new principle in the field of angle measurement but also greatly expands the applicability of TENGs as self-powered sensors.

Key words: triboelectric nanogenerators, recurrent neural network, vehicle pedal movement, quantitative model

CLC Number:

U463

ZHANG Haodong, WANG Wuhong, LU Xiao, TAN Haiqiu, JIANG Xiaobei, SHI Jian. Quantitative Model of Vehicle Pedal Movement Based on Triboelectric Nanogenerators[J]. Journal of Mechanical Engineering, 2022, 58(17): 215-225.

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