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Journal ArticleDOI

Rule based energy management strategy for a series–parallel plug-in hybrid electric bus optimized by dynamic programming

Jiankun Peng, +2 more
- 01 Jan 2017 - 
- Vol. 185, pp 1633-1643
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TLDR
In this paper, the authors employ the dynamic programming (DP) to locate the optimal actions for the engine in PHEVs, and propose a recalibration method to improve the performance of the rule-based energy management through the results calculated by DP algorithm.
About
This article is published in Applied Energy.The article was published on 2017-01-01. It has received 471 citations till now. The article focuses on the topics: Energy management & Rule-based system.

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Citations
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Journal ArticleDOI

Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle

TL;DR: In this paper, a predictive energy management strategy for a parallel hybrid electric vehicle (HEV) based on velocity prediction and reinforcement learning (RL) is presented, where Fuzzy encoding and nearest neighbor approaches are proposed to achieve velocity prediction, and a finite state Markov chain is exploited to learn transition probabilities of power demand.
Journal ArticleDOI

Continuous reinforcement learning of energy management with deep Q network for a power split hybrid electric bus

TL;DR: A novel reinforcement learning methodology into energy management for HEB which solve the curse of state variable dimensionality, and the techniques can be adopted to solve similar problems.
Journal ArticleDOI

Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus

TL;DR: This paper proposes a energy management strategy for a series-parallel plug-in hybrid electric bus based on deep deterministic policy gradients that outperforms conventional reinforcement learning approach and exhibits performance close to the global optimal dynamic programming.
Journal ArticleDOI

A novel equivalent consumption minimization strategy for hybrid electric vehicle powered by fuel cell, battery and supercapacitor

TL;DR: Compared with RBCS and HEOS, hydrogen consumption of SECMS decreases of 2.16 % and 1.47 % respectively and it also has the most smooth fuel cell current, which means a lowest fuel cell degradation.
Journal ArticleDOI

An energy management strategy based on stochastic model predictive control for plug-in hybrid electric buses

TL;DR: In this paper, a stochastic model predictive control (SMPC) based energy management strategy for plug-in hybrid electric bus (PHEB) is proposed and verified in a hardware-in-the-loop (HIL) environment.
References
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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

Classification and Review of Control Strategies for Plug-In Hybrid Electric Vehicles

TL;DR: In this paper, state-of-the-art control strategies for PHEV controllers are reviewed and classified in detail, and an analysis on which strategy is more suitable to maximize PHEV performance in different drive cycle conditions is provided.
Journal ArticleDOI

MPC-Based Energy Management of a Power-Split Hybrid Electric Vehicle

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

A Comparative Study Of Supervisory Control Strategies for Hybrid Electric Vehicles

TL;DR: This paper presents three different energy management approaches for the control of a parallel hybrid electric sport-utility-vehicle that do not require a priori knowledge of the driving cycle and shows that the A-ECMS strategy is the best performing strategy.
Journal ArticleDOI

Control of a parallel hybrid powertrain: optimal control

TL;DR: The goal of this paper is to propose an efficient tool to evaluate minimal fuel consumption that is achievable in simulation and based on optimal control theory, which can be easily applied to a large family of parallel arrangements.
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