ORCID Profile
0000-0003-4481-4893
Current Organisation
Beijing University of Technology
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Publisher: Elsevier BV
Date: 12-2023
Publisher: SAGE Publications
Date: 2013
DOI: 10.1155/2013/323917
Abstract: Dual clutch transmissions (DCTs) are recognized as being suitable for electric drive applications as they can drive with high efficiency and achieve good shifting comfort. A two-speed DCT electric drivetrain is described in this paper, comprised of only two gear pairs and a final drive gear in the two-speed gearbox. The fundamental shifting control algorithm is provided. On the testing rig of University of Technology, Sydney (UTS) powertrain lab, shifting controls and some driving cycle controls were realized. The results demonstrated that the control algorithm functioned well both in transient shifting control process and in the driving cycle conditions.
Publisher: Elsevier BV
Date: 2023
Publisher: Elsevier BV
Date: 04-2023
Publisher: Elsevier BV
Date: 09-2014
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Publisher: SAE International
Date: 14-04-2015
DOI: 10.4271/2015-01-0630
Publisher: SAE International
Date: 04-2014
DOI: 10.4271/2014-01-1799
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 10-2018
Publisher: IEEE
Date: 02-2019
Publisher: Elsevier BV
Date: 12-2016
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Elsevier BV
Date: 04-2021
Publisher: Institution of Engineering and Technology
Date: 2014
DOI: 10.1049/CP.2014.0356
Publisher: SAGE Publications
Date: 03-2019
Abstract: Aiming at improving regenerative braking ability in electric vehicles without compromising any safety, two different regenerative braking strategies are proposed in this study. The impact of continuously varying braking force distributions between front/rear wheel and electric/friction corresponding in two different strategies on braking noise are investigated. Based on the closed-loop coupling disk brake model, the relationship between the contact coupling stiffness and the braking force is established by considering the stationary modal test, the nonlinear optimization, and the relationship between brake-line pressure and braking force. The continuously varying braking force is initially transformed to continuously varying contact coupling stiffness, then, the brake noise tendency at each frequency band is calculated in closed-loop coupled model. The predicted result shows good consistency with the result recorded in bench test, verifying the reliability and effectivity of the presented method. The comparison of the two different electric braking strategies shows that the second braking strategy is superior to the first braking strategy in terms of suppressing the brake noise tendency.
Publisher: Elsevier BV
Date: 09-2019
Publisher: Elsevier BV
Date: 06-2023
Publisher: SAGE Publications
Date: 02-2018
Publisher: Elsevier BV
Date: 04-2021
Publisher: Elsevier BV
Date: 04-2023
Publisher: Elsevier BV
Date: 11-2017
Publisher: Elsevier BV
Date: 12-2017
Publisher: Elsevier BV
Date: 09-2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2019
Publisher: Elsevier BV
Date: 03-2020
Publisher: IEEE
Date: 02-2019
Publisher: Elsevier BV
Date: 03-2019
Publisher: Elsevier BV
Date: 2023
Publisher: MDPI AG
Date: 22-05-2022
DOI: 10.3390/SU14106320
Abstract: Considering the limited driving range and inconvenient energy replenishment way of battery electric vehicle, fuel cell electric vehicles (FC EVs) are taken as a promising way to meet the requirements for long-distance low-carbon driving. However, due to the limitation of FC power ability, a battery is usually adopted as the supplement power source to fill the gap between the requirement of driving and the serviceability of FC. In consequence, energy management is essential and crucial to an efficient power flow to the wheel. In this paper, a self-optimizing power matching strategy is proposed, considering the energy efficiency and battery degradation, via implementing a deep deterministic policy gradient. Based on the proposed strategy, less energy consumption and longer FC and battery life can be expected in FC EV powertrain with optimal hybridization degree.
Publisher: Elsevier BV
Date: 11-2018
Publisher: SAE International
Date: 04-2014
DOI: 10.4271/2014-01-1740
Publisher: SAGE Publications
Date: 07-02-2020
Abstract: Powertrain configuration plays an important role in the performance of plug-in hybrid electric buses. Current designs are the compromise between energy efficiency, dynamic ability, shifting smoothness and manufactural cost. To balance the above requirements, this research proposes a novel dual motor powertrain for plug-in hybrid electric buses. The efficiency improvement is compared to the conventional plug-in parallel hybrid electric buses with a single motor powertrain. Parameter designs of system components guarantee two configurations equivalently. To maximize the benefits of the proposed powertrain, this paper introduces an energy management strategy which coordinates enumeration method and dynamic programming to build the optimal maps of powertrain operation. The enumeration method determines the working points of power sources and gear states in all possible modes according to vehicle speed and power. The dynamic programming then selects the most suitable mode with the consideration of gear shifting and mode change in the optimal maps. Simulation results show that the dual motors work in peak efficiency region much more frequently than the single motor in different conditions. Therefore, the total energy cost of dual motor powertrain for entire driving cycles decreases significantly in comparison with the single motor powertrain, 6.5% in the LA92 and 6.7% in the Urban Dynamometer Driving Schedule.
Publisher: Elsevier BV
Date: 02-2021
Publisher: SAE International
Date: 05-04-2016
DOI: 10.4271/2016-01-0468
Publisher: IEEE
Date: 02-2017
Publisher: Inderscience Publishers
Date: 2018
Publisher: Inderscience Publishers
Date: 2018
Publisher: Elsevier BV
Date: 10-2018
Publisher: Elsevier BV
Date: 05-2019
Location: Australia
No related grants have been discovered for Jiageng Ruan.