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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.

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An Energy Management Strategy of Hybrid Energy Storage Systems for Electric Vehicle Applications

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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

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Energy Management Systems for Electrified Powertrains: State-of-the-Art Review and Future Trends

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Energy Management of Hybrid Electric Vehicles: 15 years of development at the Ohio State University

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.
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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

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

TL;DR: This paper introduces a generic dynamic programming function for Matlab that solves discretetime optimal-control problems using Bellman's dynamic programming algorithm.
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