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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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Proceedings ArticleDOI

Estimating energy consumption of a PHEV using vehicle and on-board navigation data

TL;DR: This paper presents a novel approach for predicting the energy consumption of a plug-in hybrid electric vehicle (PHEV) by using a polynomial model fit to the data so as to estimate the optimal energy consumption strategy from the expected driving condition, rather than using dynamic programming.
Proceedings ArticleDOI

Hybrid Systems Energy Management Using Optimization Method Based on Dynamic Sources Models

TL;DR: In this paper, the authors focus on offline energy management strategy based on dynamic losses computation made on accurate sources models, which is applied to a Fuel Cell based Vehicle (FCV) powertrain and it has been adapted to the mathematical model depending on the sources characteristics (fuel cell and battery).
Journal ArticleDOI

Effect of gear shift and engine start losses on control strategies for hybrid electric vehicles

TL;DR: In this paper, an optimal control algorithm for the start-stop, power split and gear shift problem based on Dynamic Programming-Pontryagin's Minimum Principle control approach is used to evaluate the effect of gear shift and engine start losses on the optimal solution.
Proceedings ArticleDOI

Analysis of rule-based parameterized control strategy for a HEV Hybrid Electric Vehicle

TL;DR: Two control strategies are developed and compared for different criteria as energy consumption, design and expected battery life and different energy management strategies based on rules and using batteries are proposed.
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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