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Open AccessJournal ArticleDOI

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

An efficient auxiliary system controller for Fuel Cell Electric Vehicle (FCEV)

TL;DR: In this article, an overview of the vehicle design is given as well as an in depth analysis of the powertrain efficiency and control strategy, which leads to the development of a modified powertrain control algorithm which also oversees and controls the auxiliary power demand in real-time.
MonographDOI

Evaluation, generation, and transformation of driving cycles

TL;DR: In this paper, the focus of vehicle manufacturers is on evaluating and designing of driving cycles for evaluation and design of vehicles, and indirectly they affect the environmental impact of vehicles sin sin...
Journal ArticleDOI

Long-term stochastic model predictive control for the energy management of hybrid electric vehicles using Pontryagin’s minimum principle and scenario-based optimization

TL;DR: In this paper , the authors proposed a new approach to efficiently integrate long prediction horizons subject to uncertainty into a stochastic model predictive control (MPC) framework for the energy management of hybrid electric vehicles.
Proceedings ArticleDOI

Hybrid Access Design for Femtocell Networks with Dynamic User Association and Power Control

TL;DR: A universal power control algorithm that can provide QoS support in minimum signal-to-interference-plus-noise ratios (SINRs) for all users while exploiting differentiated channel conditions to enhance the network throughput is 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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