期刊
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING
卷 234, 期 2-3, 页码 810-822出版社
SAGE PUBLICATIONS LTD
DOI: 10.1177/0954407019848190
关键词
Hybrid electric vehicle; best-mode control strategy; rule-based controller; dynamic programming; particle swarm optimization
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.
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