Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle

Geng, C.; Ning, Dawen; Guo, Linfu; Xue, Qicheng; Mei, Shujian

doi:10.3390/en14082202

Cited by 23 publications

(10 citation statements)

References 19 publications

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“…The driver's request torque and vehicle speed lookup tables are generated based on the acceleration and brake pedal position of the vehicle. 172 These lookup tables are used to calibrate the driver's request torque and vehicle's speed based on the driver's accelerating and braking inputs. 173 Also, it is used to estimate and optimize the future brake commands based on the vehicle's recent state and it enhances the vehicle's overall braking efficiency.…”

Section: Lookup Table For Driver Torque and Vehicle Speedmentioning

confidence: 99%

“…The initial phase in RBS calibration is the calculation of various vehicle variables for constructing standard speed and driver request torque lookup tables. The driver's request torque and vehicle speed lookup tables are generated based on the acceleration and brake pedal position of the vehicle 172 . These lookup tables are used to calibrate the driver's request torque and vehicle's speed based on the driver's accelerating and braking inputs 173 .…”

Section: Calibration Parameters In Regenerative Braking Systemmentioning

confidence: 99%

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Critical review on optimal regenerative braking control system architecture, calibration parameters and development challenges for EVs

Saiteja

Ashok

Wagh

et al. 2022

Intl J of Energy Research

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Summary Vehicle technology advances and the world shifts towards E‐mobility, improving the performance of electric vehicles (EVs) and HEVs, which are becoming the prominent focus. One of the prime topics of EV development is increasing the driving range, which is the fundamental requirement. Apart from increasing the battery capacity, retrieving the wasted energy during conventional braking, also called as regenerative braking, is a hot topic. In this context, numerous control architectures and major braking approaches are considered to examine in this study in order to create an efficient regenerative braking system (RBS). This review article intends to provide an overview of major subsystems in the RBS such as motor control system and hydraulic braking system and how it affects the braking performance is also well discussed. Additionally, it complies with some of the recent research applications and systematically reviews the several braking control strategies implied. The prominent ones are fuzzy logic control, neural network, MPC, sliding mode, and adaptive control modelling approaches. These control strategies are used to enhance energy regeneration without affecting vehicle performance. Further, this article discusses the RBS design process and its calibration variables, such as speed of the vehicle and brake force estimation, which can be used to improve braking performance. Moreover, challenges on RBS improvements are effectively addressed, coupled with brief suggestions and discussions for the growth of future RBS development. Finally, this article will hopefully help the reader to critically analyse the working of RBS and encourage to design of an efficient RBS for electro‐mobility application. Highlights A holistic overview of the RBS control system architecture and its various control systems is reviewed. Various brake energy control strategies like Fuzzy, MPC, NN, SMC, Adaptive and learning‐based controls are critically evaluated. The discussion of necessary calibration process and its associated parameters are elucidated. Representation of real‐time design and development process of an efficient RBS in EV. Some of the prominent challenges faced during design and development of RBS and scope of future improvement is suggested.

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Section: Lookup Table For Driver Torque and Vehicle Speedmentioning

confidence: 99%

Section: Calibration Parameters In Regenerative Braking Systemmentioning

confidence: 99%

Critical review on optimal regenerative braking control system architecture, calibration parameters and development challenges for EVs

Saiteja

Ashok

Wagh

et al. 2022

Intl J of Energy Research

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“…They achieved a braking energy recovery of 17.4% under NEDC conditions. Geng et al [26] proposed a dual-layer multi parameter control strategy for braking energy recovery, which significantly improves the energy recovery efficiency of the vehicle. Ning et al [27] proposed an energy recovery efficiency optimization algorithm based on fuzzy Q-learning.…”

Section: Introductionmentioning

confidence: 99%

A Logic Threshold Control Strategy to Improve the Regenerative Braking Energy Recovery of Electric Vehicles

Yin,

Ma,

Zhang

et al. 2023

Sustainability

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With increasing global attention to climate change and environmental sustainability, the sustainable development of the automotive industry has become an important issue. This study focuses on the regenerative braking issues in pure electric vehicles. Specifically, it intends to elucidate the influence of the braking force distribution of the front and rear axles on access to energy recovery efficiency. Combining the I curve of a pure electric vehicle and the boundary line of the Economic Commission of Europe (ECE) regulations, the braking force distribution relationship between the front and rear axles is formulated to satisfy braking stability. The maximum regenerative braking force of the motor is determined based on the motor torque characteristics and battery charging power, and the regenerative braking torque is optimized by combining the constraints of the braking strength, battery state of charge (SOC), and vehicle speed. Six road working conditions are built, including the New European Driving Cycle (NEDC), the World Light-Duty Vehicle Test Cycle (WLTC), Federal Test Procedure 72 (FTP-72), Federal Test Procedure 75 (FTP-75), the China Light-Duty Vehicle Test Cycle—Passenger (CLTC-P), and the New York City Cycle (NYCC). The efficiency of the regenerative braking strategy is validated by using the Simulink/MATLAB simulation. The simulation results show that the proposed dynamic logic threshold control strategy can significantly improve the energy recovery effect of electric vehicles, and the energy recovery efficiency can be improved by at least 25% compared to the situation without regenerative braking. Specifically, under the aforementioned road working conditions, the braking energy recovery efficiency levels are 27.69%, 42.18%, 49.54%, 47.60%, 49.28%, and 51.06%, respectively. Moreover, the energy recovery efficiency obtained by the current dynamic logic threshold is also compared with other published results. The regenerative braking control method proposed in this article makes the braking control of electric vehicles more precise, effectively reducing energy consumption and improving the driving range of electric vehicles.

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“…Achieve a total fuel saving rate of about 7%. 8 The supercapacitor and battery parallel braking energy recovery system developed by China Coal Pingshuo Group in China was applied to Komatsu 730E, and the fuel-saving rate reached 10.29%. 9 Wuhan Micro hydrogen New Energy Co., Ltd. and China Coal Pingshuo Group designed a new braking energy recovery system based on supercapacitor and battery hybrid energy storage with an energy recovery rate of up to 53.5%.…”

Section: Introductionmentioning

confidence: 99%

Research on the braking energy reuse management strategy of hybrid electric mining trucks based on motor load rate

Wang

Yang

Zhang

2023

Proceedings of the Institution of Mechanical Engineers, Part D:

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The braking energy recovery and reuse technology are significant to the energy-saving and emission reduction of hybrid mining dump trucks. Therefore, this paper proposes a technical scheme to increase the speed of the heavy-load uphill section by using the light overload of the motor. By constructing the vehicle dynamics model of the mining dump truck and the electric drive system component efficiency and engine energy consumption model and taking the “feedback braking energy-saving coefficient” as the evaluation index, the electric motors of each slope section under the rule-based energy management strategy are obtained. Then, the dynamic programing algorithm is used to optimize the selection of the motor load rate on the slope section. The results show that: on the premise of ensuring the dynamic performance of the vehicle, maximizing the use of the braking energy can shorten the driving time by 57.8 s and reduce the engine energy consumption 18.63 kWh, accounting for 8.56% of the engine energy consumption of the entire heavy-load uphill section. This paper provides a theoretical reference for the energy-saving research on the efficient reuse of braking energy of mining dump trucks on slopes.

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Simulation Research on Regenerative Braking Control Strategy of Hybrid Electric Vehicle

Cited by 23 publications

References 19 publications

Critical review on optimal regenerative braking control system architecture, calibration parameters and development challenges for EVs

Critical review on optimal regenerative braking control system architecture, calibration parameters and development challenges for EVs

A Logic Threshold Control Strategy to Improve the Regenerative Braking Energy Recovery of Electric Vehicles

Research on the braking energy reuse management strategy of hybrid electric mining trucks based on motor load rate

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