Next Article in Journal
Multivariate Temporal Convolutional Network: A Deep Neural Networks Approach for Multivariate Time Series Forecasting
Previous Article in Journal
High-Resolution Bistatic ISAR Imaging of a Space Target with Sparse Aperture
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle

Parameter Matching Optimization of a Powertrain System of Hybrid Electric Vehicles Based on Multi-Objective Optimization

1,2,*, 2,3,*, 1 and 1
1
Department of Physics, Changji College, Changji 831100, China
2
School of Control Science and Engineering, Shandong University, Jinan 250061, China
3
State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China
*
Authors to whom correspondence should be addressed.
Electronics 2019, 8(8), 875; https://doi.org/10.3390/electronics8080875
Received: 28 June 2019 / Revised: 29 July 2019 / Accepted: 5 August 2019 / Published: 7 August 2019
  |  
PDF [3721 KB, uploaded 7 August 2019]
  |  

Abstract

Aiming at problems of large computational complexity and poor reliability, a parameter matching optimization method of a powertrain system of hybrid electric vehicles based on multi-objective optimization is proposed in this paper. First, according to the vehicle basic parameters and performance indicators, the parameter ranges of different components were analyzed and calculated; then, with the weight coefficient method, the multi-objective optimization (MOO) problem of fuel consumption and emissions was transformed into a single-objective optimization problem; finally, the co-simulation of AVL Cruise and Matlab/Simulink was achieved to evaluate the effects of parameter matching through the objective function. The research results show that the proposed parameter matching optimization method for hybrid electric vehicles based on multi-objective optimization can significantly reduce fuel consumption and emissions of a vehicle simultaneously and thus provides an optimized vehicle configuration for energy management strategy research. The method proposed in this paper has a high application value in the optimization design of electric vehicles. View Full-Text
Keywords: hybrid electric vehicle; parameter matching optimization; multi-objective optimization; system modeling hybrid electric vehicle; parameter matching optimization; multi-objective optimization; system modeling
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Fu, X.; Zhang, Q.; Tang, J.; Wang, C. Parameter Matching Optimization of a Powertrain System of Hybrid Electric Vehicles Based on Multi-Objective Optimization. Electronics 2019, 8, 875.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Electronics EISSN 2079-9292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top