A Stochastic Optimal Control Approach for Power Management in Plug-In Hybrid Electric Vehicles
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This paper uses stochastic dynamic programming to optimize PHEV power management over a distribution of drive cycles, rather than a single cycle, thereby systematically exploring the potential benefits of controlled charge depletion over aggressive charge depletion followed by charge sustenance.Abstract:
This paper examines the problem of optimally splitting driver power demand among the different actuators (i.e., the engine and electric machines) in a plug-in hybrid electric vehicle (PHEV). Existing studies focus mostly on optimizing PHEV power management for fuel economy, subject to charge sustenance constraints, over individual drive cycles. This paper adds three original contributions to this literature. First, it uses stochastic dynamic programming to optimize PHEV power management over a distribution of drive cycles, rather than a single cycle. Second, it explicitly trades off fuel and electricity usage in a PHEV, thereby systematically exploring the potential benefits of controlled charge depletion over aggressive charge depletion followed by charge sustenance. Finally, it examines the impact of variations in relative fuel-to-electricity pricing on optimal PHEV power management. The paper focuses on a single-mode power-split PHEV configuration for mid-size sedans, but its approach is extendible to other configurations and sizes as well.read more
Citations
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References
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Book
Dynamic Programming and Optimal Control
TL;DR: The leading and most up-to-date textbook on the far-ranging algorithmic methododogy of Dynamic Programming, which can be used for optimal control, Markovian decision problems, planning and sequential decision making under uncertainty, and discrete/combinatorial optimization.
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Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 2. Modeling and identification
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Statistical Inference about Markov Chains
T. W. Anderson,Leo A. Goodman +1 more
TL;DR: In this article, the transition probabilities of a Markov chain of arbitrary order were obtained and their asymptotic distribution was obtained for a single observation of a long chain, and the relation between likelihood ratio criteria and contingency tables was discussed.
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Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 1. Background
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