Proceedings ArticleDOI
A-ECMS: An Adaptive Algorithm for Hybrid Electric Vehicle Energy Management
C. Musardo,Giorgio Rizzoni,Benedetto Staccia +2 more
- pp 1816-1823
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TLDR
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.Abstract:
Hybrid Electric Vehicles (HEV) improvements in fuel economy and emissions strongly depend on the energy management strategy. In this paper a new control strategy called Adaptive Equivalent Consumption Minimization Strategy (A-ECMS) is presented. This real-time energy management for HEV is obtained adding to the ECMS framework an on-the-fly algorithm for the estimation of the equivalence factor according to the driving conditions. The main idea is to 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. The results obtained with A-ECMS show that the fuel economy that can be achieved is only slightly sub-optimal and the operations are charge-sustaining.read more
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Journal ArticleDOI
Control of hybrid electric vehicles
Antonio Sciarretta,Lino Guzzella +1 more
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.
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
Stochastic MPC With Learning for Driver-Predictive Vehicle Control and its Application to HEV Energy Management
TL;DR: The proposed SMPCL approach outperforms conventional model predictive control and shows performance close to MPC with full knowledge of future driver power request in standard and real-world driving cycles.
Journal ArticleDOI
Energy Management Power Converters in Hybrid Electric and Fuel Cell Vehicles
Jih-Sheng Lai,Douglas J. Nelson +1 more
TL;DR: The significance of energy management power converters and their circuit topology options for efficiency, size, and cost considerations is described.
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.
Proceedings ArticleDOI
Equivalent consumption minimization strategy for parallel hybrid powertrains
TL;DR: An algorithm which chooses the power split between the motor and the engine in order to minimize the fuel consumption is presented and results show that a 17.5% of fuel reduction can be achieved for the CEN speed cycle.
Journal ArticleDOI
Multi-Mode Driving Control of a Parallel Hybrid Electric Vehicle Using Driving Pattern Recognition
TL;DR: In this article, the authors developed a multi-mode driving control algorithm using driving pattern recognition and applied it to a parallel hybrid electric vehicle (parallel HEV) to optimize the vehicle performances on a temporary driving pattern, which is defined as a driving cycle with grades.
Proceedings ArticleDOI
Control development for a hybrid-electric sport-utility vehicle: strategy, implementation and field test results
TL;DR: The control strategy presented and evaluated was developed for a parallel hybrid vehicle designed for the FutureTruck 2000 competition and indicates that it is possible to reduce NO/sub x/ emissions by more than 10% without significantly degrading fuel economy.