Fuel consumption reduction by introducing best-mode controller for hybrid electric vehicles

Author:

Mashadi Behrooz1,Khadem Nahvi Mahdi1ORCID

Affiliation:

1. School of Automotive Engineering, Iran University of Science & Technology, Tehran, Iran

Abstract

In this paper, a power management system for hybrid electric vehicles is developed and shown to improve the vehicle fuel consumption in various working conditions. A best-mode concept is defined based on the results of the dynamic programming global optimization strategy. It is shown that the use of exclusive control relations for each working mode improves fuel saving. The working state of the engine and one electric motor is used to determine the best-mode of powertrain operation. The best-mode classification also considers the battery state of charge. This enables the controller to specify near optimal working points in a wide range of state of charge. The control rule for each different work-mode is developed based on the dynamic programming results and applying the particle swarm optimization algorithm. The results show that the best-mode controller is capable of achieving fuel consumptions around 97% of that of the offline dynamic programming.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Aerospace Engineering

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Learning-Based Model Predictive Control for the Energy Management of Hybrid Electric Vehicles Including Driving Mode Decisions;IEEE Transactions on Vehicular Technology;2023

2. Event-triggered H∞ coordinated control based mode transition system of DM-PHEV;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2022-05-23

3. Battery High Temperature Sensitive Optimization-Based Calibration of Energy and Thermal Management for a Parallel-through-the-Road Plug-in Hybrid Electric Vehicle;Applied Sciences;2021-09-16

4. Optimal adaptive race strategy for a Formula-E car;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2021-09-15

5. On the estimation of optimal state-of-charge trajectory for plug-in hybrid electric buses using trip information;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2021-08-24

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