Title: Sound quality evaluation of pure electric vehicle with subjective and objective unified evaluation method

Authors: Xincheng Zhang; Jing Cheng; JianWei Lu; Bo Yuan; Ping Jiang; Wei Sha

Addresses: School of Automotive and Transportation Engineering, Hefei University of Technology, No. 193 Tunxi Road, Baohe District, Hefei, Anhui, 230009, China ' School of Automotive and Transportation Engineering, Hefei University of Technology, No. 193 Tunxi Road, Baohe District, Hefei, Anhui, 230009, China ' School of Automotive and Transportation Engineering, Hefei University of Technology, No. 193 Tunxi Road, Baohe District, Hefei, Anhui, 230009, China ' The Besturn Development Institute, FAW CAR CO., LTD, No. 4888 Weishan Road, Changchun High Tech Industrial Development Zone, Changchun, Jilin, 132000, China ' School of Automotive and Transportation Engineering, Hefei University of Technology, No. 193 Tunxi Road, Hefei, Anhui, 230009, China ' New Energy Vehicle Research Institute, JAC Group, No.99 Ziyun Road, Hefei, Anhui, 230009, China

Abstract: The focusing points of the sound quality of pure electric vehicle (PEV) usually depend on their operating condition. In this paper, a subjective and objective unified evaluation model for sound quality evaluation in PEV based on operating condition is proposed. Firstly, a hierarchical comparison method (HCM) is applied to subjectively evaluate the acoustic test results. Then, four psychoacoustic parameters and one evaluation index of pure tonal noise are used to objectively evaluate the noise sample. And the indicators used in different operating conditions are not the same. Finally, the sound quality evaluation models based on backpropagation neural network (BPNN) algorithm and the support vector machine (SVM) algorithm are established. The result shows that the larger the sample size, the more accurate are both models. However, when the sample size is insufficient, the accuracy of SVM model is better than the BPNN model.

Keywords: PEV; pure electric vehicle; sound quality; HCM; hierarchical comparison method; subjective and objective unified model; multiple operating conditions; BPNN; backpropagation neural network; SVM; support vector machine.

DOI: 10.1504/IJVD.2022.127024

International Journal of Vehicle Design, 2022 Vol.88 No.2/3/4, pp.283 - 303

Accepted: 22 Jun 2021
Published online: 18 Nov 2022 *

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