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Journal ArticleDOI

Optimal power split in a hybrid electric vehicle using direct transcription of an optimal control problem

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TLDR
The application of direct transcription to the case of the hybrid electric vehicle (HEV) being developed in the Applied Electronics Group (GEA) at the University of Rio Cuarto is described.
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This article is published in Mathematics and Computers in Simulation.The article was published on 2009-02-01. It has received 82 citations till now. The article focuses on the topics: Nonlinear programming & Optimal control.

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Citations
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Journal ArticleDOI

Modelling and control of hybrid electric vehicles (a comprehensive review)

TL;DR: In this paper, a comprehensive review of the literature on parallel hybrid electric vehicle modelling and control is presented, focusing primarily on contributions in the aspect of parallel hybrid vehicle modeling and control.
Journal ArticleDOI

An Energy Management Controller to Optimally Trade Off Fuel Economy and Drivability for Hybrid Vehicles

TL;DR: In this paper, drivability restrictions are included in a shortest path stochastic dynamic programming (SP-SDP) formulation of the real-time energy management problem for a prototype vehicle, where the drive cycle is modeled as a stationary, finite-state Markov chain.
Journal ArticleDOI

Optimal energy management in a dual-storage fuel-cell hybrid vehicle using multi-dimensional dynamic programming

TL;DR: In this paper, the authors proposed an optimal solution to the energy management problem in fuel-cell hybrid vehicles with dual storage buffer for fuel economy in a standard driving cycle using multi-dimensional dynamic programming (MDDP).
Journal ArticleDOI

Optimal energy management for a series–parallel hybrid electric bus

TL;DR: The results show that the energy management strategy is effective to control the engine operating in a high-efficiency region as well as to sustain the battery charge state while satisfy the drive ability.
Journal ArticleDOI

An on-line predictive energy management strategy for plug-in hybrid electric vehicles to counter the uncertain prediction of the driving cycle

TL;DR: In this paper, a dynamic-neighborhood particle swarm optimization algorithm was used in the local optimal energy management strategy of plug-in hybrid electric vehicles based on data from the prediction of the future driving cycle.
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.
Book

Computer Methods for Ordinary Differential Equations and Differential-Algebraic Equations

TL;DR: This book is a practical and mathematically well informed introduction that emphasizes basic methods and theory, issues in the use and development of mathematical software, and examples from scientific engineering applications.
Book

Practical Methods for Optimal Control Using Nonlinear Programming

TL;DR: The optimal control problem is illustrated with examples of large, sparse nonlinear programming and a comparison of optimal control problems in the context of discrete-time programming.
Proceedings ArticleDOI

Predictive energy management of a power-split hybrid electric vehicle

TL;DR: Simulation results over multiple driving cycles indicate better fuel economy over conventional strategies can be achieved and the proposed algorithm is causal and has the potential for real-time implementation.
Journal ArticleDOI

A survey of the maximum principles for optimal control problems with state constraints

TL;DR: The relations between the different sets of optimality conditions arising in Pontryagin's maximum principle are shown and the application of these maximum principle conditions is demonstrated by solving some illustrative examples.
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