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Torque Distribution Based on Dynamic Programming Algorithm for Four In-Wheel Motor Drive Electric Vehicle Considering Energy Efficiency Optimization
- Source :
- World Electric Vehicle Journal, Vol 13, Iss 10, p 181 (2022)
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- The improvement of both the stability and economy of the four in-wheel motor drive (4IWMD) electric vehicle under complex drive cycles is currently a difficult problem in this field. A torque distribution method with the comprehensive goals of optimal torque distribution and energy efficiency, considering economy through energy efficiency for the 4IWMD electric vehicle, is proposed in this paper. Each component of the 4IWMD electric vehicle is modelled. The dynamic programming (DP) control algorithm is utilized for torque distribution between the front and rear in-wheel motors to obtain optimal torque distribution and energy efficiency in the 4IWMD electric vehicle. The simulation is performed on a co-simulation platform with the software of AVL Cruise and MATLAB/Simulink, considering a straight road. Compared to the fuzzy logic control algorithm, the simulation results are very promising, as the energy consumption of the electric vehicle was reduced by 22.68%, 20.73% and 21.84% under the WLTC, NEDC and customized IM240 driving cycle conditions, respectively, with the proposed DP control algorithm. The hardware-in-the loop (HIL) experimental results also indicate that the effectiveness of the proposed DP algorithm is verified under the NEDC, WLTC and IM240 driving cycles, when a straight road is considered. The proposed DP control algorithm not only reduces the vehicle energy consumption and guarantees the optimization of torque distribution, but also increases the driving range of the vehicle.
Details
- Language :
- English
- ISSN :
- 13100181 and 20326653
- Volume :
- 13
- Issue :
- 10
- Database :
- Directory of Open Access Journals
- Journal :
- World Electric Vehicle Journal
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.7868194f41e843609eee8c80ad8a7841
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/wevj13100181