Journal ArticleDOI
Control of hybrid electric vehicles
Antonio Sciarretta,Lino Guzzella +1 more
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TLDR
In this paper, the authors analyzed two approaches, namely, feedback controllers and ECMS, which can lead to system behavior that is close to optimal, with feedback controllers based on dynamic programming.Abstract:
Global optimization techniques, such as dynamic programming, serve mainly to evaluate the potential fuel economy of a given powertrain configuration. Unless the future driving conditions can be predicted during real-time operation but the results obtained using this noncausal approach establish a benchmark for evaluating the optimality of realizable control strategies. Real-time controllers must be simple in order to be implementable with limited computation and memory resources. Moreover, manual tuning of control parameters should be avoided. This article has analyzed two approaches, namely, feedback controllers and ECMS. Both of these approaches can lead to system behavior that is close to optimal, with feedback controllers based on dynamic programming. Additional challenges stem from the need to apply optimal energy-management controllers to advanced HEV architectures, such as combined and plug-in HEVs, as well as to optimization problems that include performance indices in addition to fuel economy, such as pollutant emissions, driveability, and thermal comfortread more
Citations
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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
Optimal Control of Hybrid Electric Vehicles Based on Pontryagin's Minimum Principle
TL;DR: In static simulation for a power-split hybrid vehicle, the fuel economy of the vehicle using the control algorithm proposed in this brief is found to be very close-typically within 1%-to the fuel Economy through global optimal control that is based on dynamic programming (DP).
Journal ArticleDOI
MPC-Based Energy Management of a Power-Split Hybrid Electric Vehicle
Hoseinali Borhan,Ardalan Vahidi,Anthony Mark Phillips,Ming L. Kuang,Ilya Kolmanovsky,S. Di Cairano +5 more
TL;DR: The results of a nonlinear MPC strategy show a noticeable improvement in fuel economy with respect to those of an available controller in the commercial Powertrain System Analysis Toolkit (PSAT) software and the other proposed methodology by the authors based on a linear time-varying MPC.
Journal ArticleDOI
Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective
TL;DR: A comprehensive analysis of EMS evolution toward blended mode (BM) and optimal control is presented, providing a thorough survey of the latest progress in optimization-based algorithms and highlights certain contributions that intelligent transportation systems, traffic information, and cloud computing can provide to enhance PHEV energy management.
Proceedings ArticleDOI
A generic dynamic programming Matlab function
Olle Sundstrom,Lino Guzzella +1 more
TL;DR: This paper introduces a generic dynamic programming function for Matlab that solves discretetime optimal-control problems using Bellman's dynamic programming algorithm.
References
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Journal ArticleDOI
Power management strategy for a parallel hybrid electric truck
TL;DR: The design procedure starts by defining a cost function, such as minimizing a combination of fuel consumption and selected emission species over a driving cycle, and dynamic programming is utilized to find the optimal control actions including the gear-shifting sequence and the power split between the engine and motor while subject to a battery SOC-sustaining constraint.
Book
Vehicle Propulsion Systems: Introduction to Modeling and Optimization
Lino Guzzella,Antonio Sciarretta +1 more
TL;DR: In this article, the authors present IC-engine-based and fuel-cell-based propulsion systems for vehicle energy and fuel consumption, as well as a case study of case studies and optimal control theory.
Journal ArticleDOI
Optimal control of parallel hybrid electric vehicles
TL;DR: A model-based strategy for the real-time load control of parallel hybrid vehicles is presented and a suboptimal control is found with a proper definition of a cost function to be minimized at each time instant.
Journal ArticleDOI
A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management
TL;DR: A new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented, adding to the ECMS framework an on-the-fly algorithm for the estimation of the equivalence factor according to the driving conditions.