Journal ArticleDOI
A near–optimal rule–based energy management strategy for medium duty hybrid truck
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TLDR
In this article, a rule-based energy management strategy for a medium duty hybrid truck with a clutched clutch is presented. But the performance of the proposed energy management control strategy is studied by using a proposed longitudinal vehicle model of a pre-transmission parallel medium duty pickup with a clutch.Abstract:
This paper covers the design and implementation of a rule-based energy management strategy for a medium duty hybrid truck. In this paper, a procedure for the design of a near-optimal energy management strategy is presented. The procedure utilises the dynamic programming (DP) algorithm to find the optimal control strategy that minimises the fuel consumption over a given driving mission. Through the analysis of the behaviour of DP control actions, near-optimal rules are extracted and tuned to design a rule-based strategy for charge sustaining operation which, unlike DP control signals, is implementable on-board of the vehicle. Drivability metrics such as frequent clutching and engine on/off behaviour are also included in the control design based on the implementation of the DP under different drivability scenarios.
The performance of the proposed energy management control strategy is studied by using a proposed longitudinal vehicle model of a pre-transmission parallel medium duty hybrid truck with a clutch. The proposed near-optimal rule-based strategy, benchmarked against the optimal DP solution, shows performance within 3% of the global optimal one.read more
Citations
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An Energy Management Strategy of Hybrid Energy Storage Systems for Electric Vehicle Applications
TL;DR: An optimal energy management strategy is proposed based on the Pontryagin's minimum principle in this research, which instantaneously distributes the required propulsion power to the two ESSs during the vehicle's propulsion and also instantaneously allocates the regenerative braking energy to theTwo E SSs duringThe vehicle's braking.
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Adaptive Fuzzy Logic Energy Management Strategy Based on Reasonable SOC Reference Curve for Online Control of Plug-in Hybrid Electric City Bus
TL;DR: The effectiveness of battery energy planning by comprehensively considering the future partial trip information and historical optimal SOC curves is verified, which provides a new perspective for real vehicle energy management.
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Energy Management Systems for Electrified Powertrains: State-of-the-Art Review and Future Trends
Atriya Biswas,Ali Emadi +1 more
TL;DR: The paper delineates the chronological steps of a utilitarian EMS development, starting from theoretical background, process of simplification, validation through model-in-the-loop, software-in theloop, hardware- in theloop simulation, dynamometer test, and on-road performance validation.
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Energy Management of Hybrid Electric Vehicles: 15 years of development at the Ohio State University
Giorgio Rizzoni,Simona Onori +1 more
TL;DR: In this paper, the authors present a series of control algorithms that have been developed in simulation and implemented in prototype vehicles for charge-sustaining HEVs at OSU-CAR.
Journal ArticleDOI
A length ratio based neural network energy management strategy for online control of plug-in hybrid electric city bus
TL;DR: In this article, a novel energy management strategy that can reduce the micro-controller resources usage and achieve close to optimal control performance was proposed for online control of plug-in hybrid electric city bus, where a single parameter of length ratio was introduced to represent trip information, and a novel efficient neural network module structure was designed to reduce the calculation time and memory usage of microcontroller.
References
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Book
Optimal Control
TL;DR: Reading optimal control frank l lewis solution manual ebook pdf 2019 is extremely useful because you could get enough detailed information in the book technology has.
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.
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
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.
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.