A Multiobjective Optimization Framework for Online Stochastic Optimal Control in Hybrid Electric Vehicles [electronic resource]

• Ngôn ngữ: eng
• Ký hiệu phân loại: 629.89 Computer control
• Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2015
• Mô tả vật lý: Size: 4263-4268 : , digital, PDF file.
• Bộ sưu tập: Metadata
• ID: 266041
• Chủ đề: 1. 33 advanced propulsion systems; 2. Markov chain; 3. Parallel hybrid electric vehicle; 4. Pareto optimal solution; 5. Stochastic optimal control

Tóm tắt

The increasing urgency to extract additional efficiency from hybrid propulsion systems has led to the development of advanced power management control algorithms. For this research, we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain and show that the control policy yielding the Pareto optimal solution minimizes online the long-run expected average cost per unit time criterion. The effectiveness of the proposed solution is validated through simulation and compared with the solution derived with dynamic programming using the average cost criterion. Finally, both solutions achieved the same cumulative fuel consumption demonstrating that the online Pareto control policy is an optimal control policy.