Related references
Note: Only part of the references are listed.
Review
Computer Science, Information Systems
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Summary: In this study, a novel energy management strategy for hybrid electric vehicles (HEVs) is proposed, which considers actual driving conditions to provide near-optimal performance. The strategy defines a near-optimal equivalent factor condition and presents an iterative scheme to adjust this condition. It shows better adaptability to changes in the driving conditions with a smaller loss of optimality.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
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Wilson Perez et al.
Summary: This paper presents a look-ahead predictive energy management strategy that combines approximate dynamic programming and an adaptive equivalent consumption minimization strategy. It obtains a near-optimal solution to control the power flow through a vehicle's powertrain. Additionally, by using an artificial neural network to adapt the equivalence factor, it improves fuel economy and enables online implementation of the energy management strategy (EMS).
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Yang Gao et al.
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Zhiguo Wang et al.
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Yifan Yang et al.
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Zhiqi Guo et al.
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Summary: In this paper, a real-time cost minimization energy management strategy for fuel cell/battery-based hybrid electric vehicles is proposed using model predictive control. Results show that the strategy can effectively reduce operating costs and extend fuel cell lifetime, demonstrating good real-time practicality.
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