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Energy management strategies for vehicular electric power systems

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TLDR
An extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments is presented.
Abstract
In the near future, a significant increase in electric power consumption in vehicles is expected. To limit the associated increase in fuel consumption and exhaust emissions, smart strategies for the generation, storage/retrieval, distribution, and consumption of electric power will be used. Inspired by the research on energy management for hybrid electric vehicles (HEVs), this paper presents an extensive study on controlling the vehicular electric power system to reduce the fuel use and emissions, by generating and storing electrical energy only at the most suitable moments. For this purpose, both off-line optimization methods using knowledge of the driving pattern and on-line implementable ones are developed and tested in a simulation environment. Results show a reduction in fuel use of 2%, even without a prediction of the driving cycle being used. Simultaneously, even larger reductions of the emissions are obtained. The strategies can also be applied to a mild HEV with an integrated starter alternator (ISA), without modifications, or to other types of HEVs with slight changes in the formulation.

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Journal ArticleDOI

Trip Based Near Globally Optimal Power Management of Plug-in Hybrid Electric Vehicles Using Gas-Kinetic Traffic Flow Model

TL;DR: In this article, a gas-kinetic base trip modeling approach was used for the highway portion trip and for the local road portion the traffic light sequences throughout the trip will be synchronized with the vehicle operation.
Journal ArticleDOI

Adaptive ECMS: a Causal Set-theoretic Method for Equivalence Factor Estimation∗

TL;DR: In this article, the equivalence factor in the equivalent consumption minimization strategies (ECMS) is estimated using an online estimation procedure, where the estimation procedure localizes a nonincreasing interval containing the correct equivalence factors.
Journal ArticleDOI

Optimal energy management for hybrid electric aircraft

TL;DR: It is shown that an optimisation-based control strategy can provide significant fuel savings over heuristic energy management strategies in this context and be used to define a predictive energy management control law.
Journal ArticleDOI

Development of route information based driving control algorithm for a range-extended electric vehicle

TL;DR: In this paper, a route information based driving control algorithm was developed for an RE-EV which consists of two motorgenerators, MG1 and MG2, for an optimization process using route information, such as vehicle velocity and altitude.
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

Practical Methods of Optimization

TL;DR: The aim of this book is to provide a Discussion of Constrained Optimization and its Applications to Linear Programming and Other Optimization Problems.
Book

Predictive Control With Constraints

TL;DR: A standard formulation of Predictive Control is presented, with examples of step response and transfer function formulations, and a case study of robust predictive control in the context of MATLAB.
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