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Application of Dynamic Programming Algorithm Based on Model Predictive Control in Hybrid Electric Vehicle Control Strategy

Xiaokan Wang*, Qiong Wang
Henan Mechanical and Electrical Vocational College, Zhengzhou, 451191, China
* Corresponding Author: Xiaokan Wang. Email:

Journal on Internet of Things 2020, 2(2), 81-87. https://doi.org/10.32604/jiot.2020.010225

Received 01 January 2020; Accepted 05 May 2020; Issue published 14 September 2020

Abstract

A good hybrid vehicle control strategy cannot only meet the power requirements of the vehicle, but also effectively save fuel and reduce emissions. In this paper, the construction of model predictive control in hybrid electric vehicle is proposed. The solving process and the use of reference trajectory are discussed for the application of MPC based on dynamic programming algorithm. The simulation of hybrid electric vehicle is carried out under a specific working condition. The simulation results show that the control strategy can effectively reduce fuel consumption when the torque of engine and motor is reasonably distributed, and the effectiveness of the control strategy is verified.

Keywords

State of charge; model predictive control; dynamic programming algorithm; optimization

Cite This Article

X. Wang and Q. Wang, "Application of dynamic programming algorithm based on model predictive control in hybrid electric vehicle control strategy," Journal on Internet of Things, vol. 2, no.2, pp. 81–87, 2020.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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