Fault Alarms and Power Performance in Hybrid Electric Vehicles Based on Hydraulic Technology

Author:

You Zhuan

Abstract

In order to improve the fault alarm effect on the power performance of hydraulic hybrid electric vehicles (HEV), this paper proposes a fault alarm method for hybrid electric vehicle power performance based on hydraulic technology, builds a hybrid electric vehicle power system model, uses hydraulic technology to extract the characteristic signals of key components, uses support vector mechanisms to build a hybrid electric vehicle classifier, and obtains the fault alarm results for dynamic performance based on hydraulic technology. The results show that the proposed method can improve real-time diagnosis and alarm for engine faults in HEV, and the fault can be diagnosed after 5 s of injection, thus ensuring the dynamic stability of HEV.

Funder

“Qinglan Project” Funding Project of Jiangsu Colleges and Universities

Research Project of Professor or Doctor in Wuxi Institute of Technology

Publisher

MDPI AG

Subject

Automotive Engineering

Reference23 articles.

1. Energy Management Strategy of Hybrid Electric Vehicle Based on ECMS in Intelligent Transportation Environment;Hou;IFAC-Pap.,2021

2. Investigation of Accumulator Main Parameters of Hydraulic Excitation System;Wu;J. Coast. Res.,2019

3. Modeling and Simulation of a New Transmission Structure for Heavy-Duty Hybrid Electric Vehicles;Chen;Comput. Simul.,2019

4. Sensor Fault Detection and Isolation Using a Support Vector Machine for Vehicle Suspension Systems;Jeong;IEEE Trans. Veh. Technol.,2020

5. Power Distribution Method for a Parallel Hydraulic-Pneumatic Hybrid System using a Piecewise Function;Nie;Energy,2021

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