Development of a Cooperative Braking System for Front-Wheel Drive Electric Vehicles

Zhao, Di; Liang, Chao; Xu, Nan; Sun, Cheng; Xu, Yanwu

doi:10.3390/en11020378

Cited by 25 publications

(13 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…When the regenerative braking system carries out energy recovery, the hydraulic braking system needs to accurately respond to the target pressure for the vehicle braking safety [19,20]. Aiming at the two working modes of the fully decoupled regenerative braking system, this paper proposes the pressure control algorithm, based on P-V characteristics, and the pressure control algorithm, based on the overflow characteristics of the solenoid valve.…”

Section: Pressure Control Algorithmmentioning

confidence: 99%

“…Among the above three forces, the electromagnetic force is related to the position of the spool and the coil current [24], which can be calculated by Formula (19). The spring force is related to spring stiffness, preload, and displacement, while the hydraulic force is related to spool stress area and hydraulic pressure.…”

Section: The Pressure Control Algorithm Based On Overflow Characteristics Of the Solenoid Valvementioning

confidence: 99%

See 1 more Smart Citation

Research on Pressure Control Algorithm of Regenerative Braking System for Highly Automated Driving Vehicles

Liang

Zhao

et al. 2021

WEVJ

Self Cite

View full text Add to dashboard Cite

Conclusive evidence has demonstrated the critical importance of highly automated driving systems and regenerative braking systems in improving driving safety and economy. However, the traditional regenerative braking system cannot be applied to highly automated driving vehicles. Therefore, this paper proposes a fully decoupled regenerative braking system for highly automated driving vehicles, which has two working modes: conventional braking and redundant braking. Aimed at the above two working modes, this paper respectively proposes the pressure control algorithm, based on P-V characteristics, and the pressure control algorithm, based on the overflow characteristics of the solenoid valve. AMESim is utilized as the simulation platform, and then is co-simulated with MATLAB/Simulink, which is embedded with the control algorithm. The simulation results show the feasibility and effectiveness of the regenerative braking system and the pressure control algorithm.

show abstract

Section: Pressure Control Algorithmmentioning

confidence: 99%

Section: The Pressure Control Algorithm Based On Overflow Characteristics Of the Solenoid Valvementioning

confidence: 99%

Research on Pressure Control Algorithm of Regenerative Braking System for Highly Automated Driving Vehicles

Liang

Zhao

et al. 2021

WEVJ

Self Cite

View full text Add to dashboard Cite

show abstract

“…As more intelligent driver assistants, in order to avoid the occurrence of false interventions and mismatch situations, and increase the driver's adaptability and trust to the vehicle, these systems should effectively obtain the driver's intentions [5][6][7]. At the same time, driving intentions have also been used in the electrohydraulic composite braking control system of electric vehicles in order to improve braking safety, energy utilization and increase driving range [8][9][10][11]. When slight braking is recognized, braking force is generated only by the motor regenerative braking system to increase energy utilization.…”

Section: Introductionmentioning

confidence: 99%

Identification of Driver Braking Intention Based on Long Short-Term Memory (LSTM) Network

Wang

Zhao

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Driving intention identification is a key technology which can improve the adaptability of the intelligent driver assistance systems and the energy efficiency of electric vehicles. This article proposes a novel method for identifying the driver braking intention. In order to improve the identification accuracy of driving intention, a braking intention identification model based on Long Short-Term Memory (LSTM) Network is constructed. The data of slight braking, normal braking and hard braking that can use for offline training are obtained through tests on real vehicle at Chang'an University vehicle performance testing ground. Support vector machine-recursive feature elimination (SVM-RFE) algorithm is used to select the characteristic parameter of braking intention identification model. The random search is subsequently used to optimize the hyper-parameters of LSTM. LSTM-based and General Hidden Markov Model (GHMM)-based model under different time window are used to identify braking intention of slight braking, normal braking and hard braking respectively. The results show that the Precision, Recall, F-measure, Accuracy of the braking intention identification model which propose in this paper based on LSTM are better than that of the braking intention identification model based on GHMM. Moreover, the Recall and Accuracy of the LSTM-based braking intention identification models are above 0.95, indicating the good ability of intention identification.

show abstract

“…In fact, the utilization of RBE in electric vehicle has been widely studied [21][22][23]. The RBE can be stored in the battery and used to power the electric vehicle in turn [24], which is controlled by the battery energy management (BMS). In order to use the maximum RBE, many control strategies have been proposed [23,[25][26][27].…”

Section: Introductionmentioning

confidence: 99%

An Optimized Regulation Scheme of Improving the Effective Utilization of the Regenerative Braking Energy of the Whole Railway Line

Gao

et al. 2019

Energies

View full text Add to dashboard Cite

With respect to the problems of great impact on the utility grid, the increasing catenary voltage, the limited utilization rate of the regenerative braking energy (RBE) and the irreducible cost of electricity for locomotives caused by the RBE generated by electric locomotives of the whole railway line cannot be fully utilized in traction power supply systems. An energy management system (EMS) integrating electrical energy and information is proposed in this paper. A corresponding optimization algorithm is also proposed to calculate the distribution of the regenerative braking power in the whole railway line. The structure and working principle of the EMS are introduced. The basic principle and detailed steps of the proposed algorithm are given. Finally, the optimization calculation and simulation are carried out, the effectiveness and feasibility of the proposed EMS and the optimization algorithm are verified.

show abstract

Development of a Cooperative Braking System for Front-Wheel Drive Electric Vehicles

Cited by 25 publications

References 21 publications

Research on Pressure Control Algorithm of Regenerative Braking System for Highly Automated Driving Vehicles

Research on Pressure Control Algorithm of Regenerative Braking System for Highly Automated Driving Vehicles

Identification of Driver Braking Intention Based on Long Short-Term Memory (LSTM) Network

An Optimized Regulation Scheme of Improving the Effective Utilization of the Regenerative Braking Energy of the Whole Railway Line

Contact Info

Product

Resources

About