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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

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Patent

Method, Apparatus, Signals and Media, for Selecting Operating Conditions of a Genset

TL;DR: In this paper, a method and apparatus for selecting optimal operating conditions of a genset is described, where an engine coupled to an electrical power generator, the gensets having a plurality of operating points each including an engine speed value and a generator electrical power output value, and the cost values associated with operating at respective operating points.
Proceedings ArticleDOI

Neural learning of driving environment prediction for vehicle power management

TL;DR: A prediction model, an effective set of features to characterize different types of roadways, and a neural network trained for online prediction of roadway types and traffic congestion levels were developed and used in conjunction with a power management strategy in a conventional vehicle.
Journal ArticleDOI

Variable structure battery-based fuel cell hybrid power system and its incremental fuzzy logic energy management strategy

TL;DR: A variable structure battery (VSB) scheme is proposed to enhance the hybrid power system, and an incremental fuzzy logic method is developed by considering the efficiency and power change rate of fuel cell to balance the power system load.
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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