Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application

This paper presents a method for compiling the load spectrum of the transmission assembly of plug-in hybrid electric vehicles (PHEVs). Based on the analysis of the control strategy of the test vehicle, the power flow transmission route in the transmission assembly is different under different operat...

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Main Authors: Baoqi Ma, Chongyang Han, Weibin Wu, Zhiheng Zeng, Chenyang Wan, Zefeng Zheng, Zhibiao Hu
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Machines
Subjects:
Online Access:https://www.mdpi.com/2075-1702/10/7/578
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author Baoqi Ma
Chongyang Han
Weibin Wu
Zhiheng Zeng
Chenyang Wan
Zefeng Zheng
Zhibiao Hu
author_facet Baoqi Ma
Chongyang Han
Weibin Wu
Zhiheng Zeng
Chenyang Wan
Zefeng Zheng
Zhibiao Hu
author_sort Baoqi Ma
collection DOAJ
description This paper presents a method for compiling the load spectrum of the transmission assembly of plug-in hybrid electric vehicles (PHEVs). Based on the analysis of the control strategy of the test vehicle, the power flow transmission route in the transmission assembly is different under different operation modes, so it is necessary to divide different load spectrum blocks according to the operation mode. Based on the big data survey of China’s national standard, it is determined that the typical working conditions are urban road working conditions, high-speed road working conditions, provincial road working conditions and poor road conditions. The mileage proportion of the various working conditions is 55:30:10:5, and the mileage of one cycle is 300 km. A total of three cycles are collected. After data processing and time-domain verification, based on the principle of maximum damage, the cycle with the largest pseudo damage is selected as the sample load data for load spectrum extrapolation. The rain flow counting method is used to count the sample load, and a two-dimensional kernel density estimation mathematical model with adaptive bandwidth is established to estimate the probability density function of the data. The extrapolated rain flow matrix is obtained through Monte Carlo simulation. The load spectrum of the two-dimensional rain flow matrix is transformed into a one-dimensional eight-stage program load spectrum by using a variable mean method, Goodman equation and equal damage principle theory. Finally, the fatigue life of the transmission assembly is simulated and calculated under the environment of Romax Designer simulation software. The two-dimensional kernel density estimation model with adaptive bandwidth is used to fit and extrapolate the load rain flow matrix of each hybrid mode of the PHEV, which solves the problem wherein the shape of the rain flow matrix of each hybrid mode of the hybrid electric vehicle is complex and difficult to fit. Finally, taking the after-sales maintenance data of this model from 2020 to the present as auxiliary proof, the failure components and the failure mileage life of the simulation test results are consistent with the results used by the actual users. This shows that the kernel density estimation model proposed in this paper can well fit the rain flow matrix of the PHEV load spectrum. The extrapolated load spectrum based on this model has high accuracy and authenticity. The method of compiling the load spectrum of the transmission assembly of a hybrid electric vehicle in this paper is effective.
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spelling doaj.art-652cccebea2e45d9bad337a6662064682023-11-30T21:19:29ZengMDPI AGMachines2075-17022022-07-0110757810.3390/machines10070578Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation ApplicationBaoqi Ma0Chongyang Han1Weibin Wu2Zhiheng Zeng3Chenyang Wan4Zefeng Zheng5Zhibiao Hu6College of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaCollege of Engineering, South China Agricultural University, Guangzhou 510642, ChinaThis paper presents a method for compiling the load spectrum of the transmission assembly of plug-in hybrid electric vehicles (PHEVs). Based on the analysis of the control strategy of the test vehicle, the power flow transmission route in the transmission assembly is different under different operation modes, so it is necessary to divide different load spectrum blocks according to the operation mode. Based on the big data survey of China’s national standard, it is determined that the typical working conditions are urban road working conditions, high-speed road working conditions, provincial road working conditions and poor road conditions. The mileage proportion of the various working conditions is 55:30:10:5, and the mileage of one cycle is 300 km. A total of three cycles are collected. After data processing and time-domain verification, based on the principle of maximum damage, the cycle with the largest pseudo damage is selected as the sample load data for load spectrum extrapolation. The rain flow counting method is used to count the sample load, and a two-dimensional kernel density estimation mathematical model with adaptive bandwidth is established to estimate the probability density function of the data. The extrapolated rain flow matrix is obtained through Monte Carlo simulation. The load spectrum of the two-dimensional rain flow matrix is transformed into a one-dimensional eight-stage program load spectrum by using a variable mean method, Goodman equation and equal damage principle theory. Finally, the fatigue life of the transmission assembly is simulated and calculated under the environment of Romax Designer simulation software. The two-dimensional kernel density estimation model with adaptive bandwidth is used to fit and extrapolate the load rain flow matrix of each hybrid mode of the PHEV, which solves the problem wherein the shape of the rain flow matrix of each hybrid mode of the hybrid electric vehicle is complex and difficult to fit. Finally, taking the after-sales maintenance data of this model from 2020 to the present as auxiliary proof, the failure components and the failure mileage life of the simulation test results are consistent with the results used by the actual users. This shows that the kernel density estimation model proposed in this paper can well fit the rain flow matrix of the PHEV load spectrum. The extrapolated load spectrum based on this model has high accuracy and authenticity. The method of compiling the load spectrum of the transmission assembly of a hybrid electric vehicle in this paper is effective.https://www.mdpi.com/2075-1702/10/7/578plug-in hybrid vehicletransmission assemblyload spectrumadaptive bandwidth kernel density estimationsimulation application
spellingShingle Baoqi Ma
Chongyang Han
Weibin Wu
Zhiheng Zeng
Chenyang Wan
Zefeng Zheng
Zhibiao Hu
Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application
Machines
plug-in hybrid vehicle
transmission assembly
load spectrum
adaptive bandwidth kernel density estimation
simulation application
title Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application
title_full Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application
title_fullStr Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application
title_full_unstemmed Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application
title_short Compilation of Load Spectrum of PHEV Transmission Assembly and Its Simulation Application
title_sort compilation of load spectrum of phev transmission assembly and its simulation application
topic plug-in hybrid vehicle
transmission assembly
load spectrum
adaptive bandwidth kernel density estimation
simulation application
url https://www.mdpi.com/2075-1702/10/7/578
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