Journal Article10.1109/MCS.2007.338280
Control of hybrid electric vehicles
Antonio Sciarretta,Lino Guzzella +1 more
1K
TL;DR: 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.
read more
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 comfort
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
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).
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.
717
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.
707
A generic dynamic programming Matlab function
Olle Sundstrom,Lino Guzzella +1 more
- 08 Jul 2009
TL;DR: This paper introduces a generic dynamic programming function for Matlab that solves discretetime optimal-control problems using Bellman's dynamic programming algorithm.
663
A Comparative Analysis of Energy Management Strategies for Hybrid Electric Vehicles
TL;DR: In this article, the authors present a formalization of the energy management problem in hybrid electric vehicles and a comparison of three known methods for solving the resulting optimization problem: dynamic programming, Pontryagin's minimum principle (PMP), and equivalent consumption minimization strategy (ECMS).
References
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
- 30 Oct 2007
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.
1.1K
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.
956
A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management
C. Musardo,Giorgio Rizzoni,Benedetto Staccia +2 more
- 12 Dec 2005
TL;DR: In this paper, a new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented, which periodically refresh the control parameter according to the current road load, so that the battery State of Charge (SOC) is maintained within the boundaries and the fuel consumption is minimized.
947