Soft Actor-Critic Algorithm-Based Energy Management Strategy for Plug-In Hybrid Electric Vehicle

Li, Tao; Cui, Wei; Cui, Naxin

doi:10.3390/wevj13100193

Cited by 8 publications

(4 citation statements)

References 51 publications

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“…However, empirical research on NLP-based ECMS is also important. For empirical verification, it is necessary to compare NLP-based ECMS with other online optimization approaches, such as PSO [21][22][23] or NN-based method [27][28][29][30][31]. We are conducting a follow-up study for empirical verification of NLP-based ECMS.…”

Section: Discussionmentioning

confidence: 99%

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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: Discussionmentioning

confidence: 99%

“…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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“…The energy management strategy has an important impact on the fuel economy, power performance, and lifespan of the power source of the hybrid tractor [11,12]. Currently, energy management strategies are basically divided into three categories: rule-based energy management strategies, learning-based energy management strategies, and optimizationbased energy management strategies [13].…”

Section: Introductionmentioning

confidence: 99%

Research on Energy Management Strategy for Series Hybrid Tractor under Typical Operating Conditions Based on Dynamic Programming

Yan,

Zhao,

Liu

et al. 2024

WEVJ

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In response to the issues of hybrid tractors’ energy management strategies, such as reliance on experience, difficulty in achieving optimal control, and incomplete analysis of typical operating conditions of tractors, an energy management strategy based on dynamic programming is proposed in combination with various typical operating conditions of tractors. This is aimed at providing a reference for the modeling and energy management strategies of series hybrid tractors. Taking the series hybrid tractor as the research object, the tractor dynamics models under three typical working conditions of plowing, rotary tillage, and transportation were established. With the minimum total fuel consumption of the tractor as the optimization target, the engine power as the control variable, and the state of charge of the power battery as the state variable, an energy management strategy based on a dynamic programming algorithm was established and simulation experiments were conducted. The simulation results show that, compared with the power-following energy management strategy, the energy management strategy based on the dynamic programming algorithm can reasonably control the operating state of the engine. Under the three typical working conditions of plowing, rotary tillage, and transportation, the battery SOC consumption increased by approximately 8.37%, 7.24%, and 0.77%, respectively, while the total fuel consumption decreased by approximately 25.28%, 21.54%, and 13.24%, respectively.

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“…As the core control strategy of hybrid tractor, energy management strategy has a direct impact on the power, economy, comfort, and emission of the whole machine, so it has become the focus and difficulty of research in the field of hybrid electric vehicles [9].…”

Section: Introductionmentioning

confidence: 99%

Research on Global Optimal Energy Management Strategy of Agricultural Hybrid Tractor Equipped with CVT

Zhang

Feng

Liu³

et al. 2023

WEVJ

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This paper presents a proposed global optimal energy management strategy based on dynamic programming to enhance the energy consumption efficiency of an agricultural hybrid tractor that is equipped with a continuously variable transmission (CVT). Firstly, using a diesel-electric parallel agricultural hybrid tractor as the research object, a tractor-rotary tillage coupling dynamics model is constructed. Secondly, with the torque and speed of the motor, the torque and speed of the diesel engine, and the CVT speed ratio as the control variables, the state of charge (SOC) of the power battery as the state variable, and the goal of minimizing the total energy consumption of the whole machine, a global optimal energy management model based on dynamic programming is established. Finally, the field operation measured data is injected into the MATLAB simulation model, and experiments are carried out to verify the effectiveness of the energy management strategy. The results show that compared with the power-following energy management strategy, the proposed energy management strategy can make the diesel engine and electric motor work in the optimal area, and effectively reduce the total cost of energy consumption of the tractor during field operations. Under the condition of rotary tillage, the total cost of energy consumption is decreased by 16.89%.

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Soft Actor-Critic Algorithm-Based Energy Management Strategy for Plug-In Hybrid Electric Vehicle

Cited by 8 publications

References 51 publications

A New HEV Power Distribution Algorithm Using Nonlinear Programming

A New HEV Power Distribution Algorithm Using Nonlinear Programming

Research on Energy Management Strategy for Series Hybrid Tractor under Typical Operating Conditions Based on Dynamic Programming

Research on Global Optimal Energy Management Strategy of Agricultural Hybrid Tractor Equipped with CVT

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