Ran Tao

Dr. Ran Tao

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 June 2025 in IEEE Transactions on Transportation Electrification
Verified
Journal Article
Closed access
RTRan Tao
Ran Tao
Wei WangWei Wang
Wei Wang
YJYufeng Jiang
Yufeng Jiang
CTChen Tang
Chen Tang
Ying FanYing Fan
Ying Fan
Wei HuaWei Hua
Wei Hua
This paper proposes a Free-Current-Curve fault-tolerant control (FCC-FTC) method for a Dual Three-Phase Permanent Magnet Synchronous Motor (DT-PMSM) drive system under an open-phase fault. In the proposed FCC-FTC, apart from the basic operational constraints (e.g., limiting the RMS phase currents, ensuring torque, and maintaining zero current sum), no sinusoidal phase current constraint is involved while the fault-tolerance performances can be optimized with maximum freedom. According to different torque output command, the proposed FCC-FTC method can be switched between the Loss Mode and the Torque Mode. In the Loss Mode, the system copper loss can be minimized. In the Torque Mode, the system torque capacity can be maximized. Compared with existing methods, the proposed FCC-FTC method has lower copper loss and stronger torque output capability. An experiment platform is set up on a DT-PMSM, and the effectiveness of the proposed FCC-FTC is validated by experimental results.

7 October 2022 in IET Electric Power Applications
Verified
Journal Article
Open access
XZXiao Zhang
Xiao Zhang
RTRan Tao
Ran Tao
ZDZhaoyu Dou
Zhaoyu Dou
SQShuo Qiu
Shuo Qiu
JLJia Liu
Jia Liu
YLYi Liu
Yi Liu
Finite control set model predictive control (FCS‐MPC) is becoming an important control method in the high‐performance control of permanent magnet synchronous motor (PMSM) because of its simple concept, easy implementation, and strong performance. However, the traditional FCS‐MPC uses only one basic voltage vector in the whole control cycle, so its steady‐state control performance is poor. In addition, FCS‐MPC relies significantly on machine parameter correctness. The performance is significantly degraded if the controller parameters do not match the real machine parameters. This study proposed a PMSM fast two‐vector model‐free predictive control approach to address the abovementioned issues. The process employs no motor parameters and relies only on the system's inputs and outputs. In addition, this method combines the fast vector selection with the two‐vector control method, which simplifies the computational effort while improving the steady‐state control accuracy at the same time. MATLAB/Simulink built the control system model, the simulation and experimental studies were carried out. The simulation and experimental results confirm the effectiveness of this method.

11 May 2022 in Journal of Electrical Engineering & Technology
Verified
Journal Article
Closed access
PDF file
XZXiao Zhang
Xiao Zhang
RTRan Tao
Ran Tao
XXXiaoming Xu
Xiaoming Xu
TWTingjie Wang
Tingjie Wang
HZHui Zhang
Hui Zhang

18 October 2022 in IET Power Electronics
Verified
Journal Article
Open access
HZHui Zhang
Hui Zhang
RTRan Tao
Ran Tao
ZLZhiliang Li
Zhiliang Li
XZXiao Zhang
Xiao Zhang
ZMZhixun Ma
Zhixun Ma
The conventional single variable indirect model predictive control (SIMPC) of LCL‐type three‐level grid‐ connected inverter (GCI) is to indirectly control the grid current by controlling the output current of the inverter, which usually produces large errors and reduces the system anti‐disturbance performance. Although the previously proposed multivariable weighted model predictive control (MWMPC) method of LCL‐type GCI can directly control many variables, such as grid current, it requires setting the weight coefficient for each variable and involves a substantial amount of calculation. To due with these problems, this paper proposes a multivariable sequential model predictive control (MSMPC) method for LCL‐type three‐level GCI. The inverter output current, the filter capacitor voltage, and the grid current are gradually predicted and optimized under the variable control sequence of the LCL‐type GCI mathematical model. Under the premise of achieving direct control of the variables above, this method can reduce the number of weighting coefficients and gradually contract the optimization space to reduce the computation required for multivariable prediction and optimization. This paper compares the proposed MSMPC to the conventional SIMPC and MWMPC in steady state, transient state performance, and anti‐disturbance performance. The effectiveness of the proposed MSMPC is demonstrated through simulation and experimentation.

1 July 2026 in IEEE Transactions on Power Electronics
Verified
Journal Article
Closed access
Lei ZhangLei Zhang
Lei Zhang
RTRan Tao
Ran Tao
XLXiaocong Li
Xiaocong Li
Driven by the electrification of transportation, there is a growing demand for high-performance control strategies in electric traction systems, particularly for Permanent Magnet Synchronous Motors (PMSMs). However, variations in internal parameters and external disturbances can significantly degrade control performance. To address these challenges, this paper introduces a novel Model-Free Adaptive Second-Order Sliding Mode Control (NMF-ASOSMC) strategy. First, an ultra-local model of the system is derived from a detailed analysis of PMSM dynamics. A second-order sliding mode speed controller is then designed, replacing the traditional switching function with a terminal attractor and integrating an adaptive law to minimize chattering. Furthermore, a sliding mode observer is employed to estimate disturbances in the speed loop in real time and provide appropriate compensation. Experimental results demonstrate the effectiveness and feasibility of the proposed strategy in improving control performance.

17 November 2025 in IEEE Transactions on Transportation Electrification
Verified
Journal Article
Closed access
RTRan Tao
Ran Tao
Wei WangWei Wang
Wei Wang
CLChengYuan Luo
ChengYuan Luo
LSLe Sun
Le Sun
Ming ChengMing Cheng
Ming Cheng
A full-torque copper-loss minimum adaptive fault-tolerant control (FTCM-AFTC) method is proposed in this article for a dual three-phase permanent magnet synchronous motor (DTP-PMSM) drive system under an open-phase fault. In the proposed FTCM-AFTC, a unified control architecture is constructed to realize seamless operation under healthy and fault conditions. The proposed FTCM-AFTC method can smoothly transition after fault occurrence without additional hardware. In addition, the method can dynamically adjust FTCM according to torque demand to ensure optimal operation efficiency. Finally, the effectiveness of the proposed FTCM-AFTC method is verified by the experimental results.