Design of Real-Time Control Based on DP and ECMS for PHEVs

Wang, Wei; Cai, Zexiang; Liu, Shaofei

doi:10.1155/2021/6667614

Cited by 5 publications

(1 citation statement)

References 27 publications

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“…An A-ECMS adjusts the equivalent factor so that the SOC can follow the reference SOC trajectory while considering driving conditions. To obtain the reference SOC trajectory, researchers have applied particle swarm optimization (PSO) [21][22][23], approximate DP [24][25][26], and neural networks (NN) [27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

A New HEV Power Distribution Algorithm Using Nonlinear Programming

Lee

2022

Applied Sciences

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An equivalent consumption minimization strategy (ECMS) is one of the most powerful and practical ways to improve the fuel efficiency of hybrid electric vehicles (HEVs). In an ECMS, it is important to determine the optimal equivalent factor to reach a global optimal solution. The optimal equivalent factor is determined by driving conditions. Previous studies have used an adaptive ECMS (A-ECMS) to determine the appropriate equivalent factor according to changing driving conditions. An A-ECMS adjusts the equivalent factor by controlling the battery’s state of charge (SOC) to follow a reference SOC trajectory. It is therefore critical to identify a reference SOC trajectory that reflects real-world driving conditions. These conditions, which are composed of the HEV’s nonlinear dynamics and complex constraints, can be formulated into a nonlinear optimal control problem (NOCP). Here, we propose applying nonlinear programming (NLP) to an A-ECMS. The NLP-based ECMS algorithm can be divided into two parts: the use of an NLP to solve an NOCP to obtain the reference SOC trajectory and the application of an NLP solution (the result of the first part) to an A-ECMS. Simulation results demonstrate that the proposed NLP-based ECMS closely resembles a global optimal solution for dynamic programming in a relatively brief calculation time.

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Section: Introductionmentioning

confidence: 99%

A New HEV Power Distribution Algorithm Using Nonlinear Programming

Lee

2022

Applied Sciences

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Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter

Feng

Chen

2022

SN Appl. Sci.

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The battery/ultracapacitor hybrid power supply system can solve the problems of high cost and short life of a single power system, and the energy management of hybrid power system has become a vital issue in the field of electric vehicles. In this paper, a fuzzy energy management strategy on the state-of-charge (SOC) estimation of power battery is proposed. Particle filter (PF) algorithm is used to estimate SOC of power battery, then estimated result is regarded as the input variable of fuzzy energy management controller, and the energy distribution result is obtained after fuzzy logic operation. The simulation results show that the SOC estimation result of the PF algorithm is closer to the actual value of power battery SOC. When the SOC estimation result of PF is embedded into the fuzzy controller for joint simulation, it is found that the charge and discharge current, and SOC consumption of the power battery are reduced, which shows the algorithm’s effectiveness. It also provides a specific reference value for the further study of the power supply control strategy of hybrid electric vehicles.

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Energy Management Strategy for Plug-In Hybrid Electric Vehicles Based on Driving Condition Recognition: A Review

Liu

Yan

2022

Electronics

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Appropriate energy management strategies (EMSs) have been selected for plug-in hybrid electric vehicles (PHEVs) based on driving-condition recognition (DCR) according to the acquired driving information, so as to minimize the target parameters. With online control and offline optimization, the strategy is suitable for real-time applications and is of great significance to repetitive routes, owing to its simplicity and ease of implementation. This paper aims to identity the DCR-based EMSs, develop efficient EMSs, and invite researchers involved in this field to discover new solutions. This paper presents a comprehensive analysis of EMSs based on DCR in terms of principles, the scope of application as well as their advantages and disadvantages, and provides a thorough survey of the latest progress in EMSs. We concluded that DCR-based EMSs show an improvement in energy saving and the pollutant-discharging effect.

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Design of Real-Time Control Based on DP and ECMS for PHEVs

Cited by 5 publications

References 27 publications

A New HEV Power Distribution Algorithm Using Nonlinear Programming

A New HEV Power Distribution Algorithm Using Nonlinear Programming

Fuzzy energy management strategy for hybrid electric vehicles on battery state-of-charge estimation by particle filter

Energy Management Strategy for Plug-In Hybrid Electric Vehicles Based on Driving Condition Recognition: A Review

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