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Author

Qiu Feng

Bio: Qiu Feng is an academic researcher from Northeast Forestry University. The author has contributed to research in topics: Torque & Electromagnetic coil. The author has an hindex of 1, co-authored 4 publications receiving 6 citations.

Papers
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Journal ArticleDOI
TL;DR: An improved torque control method of an EPS motor based on the improved ADRC is proposed, which has good motor current stability, steering torque smoothness, and flexibility when there is low-frequency disturbance.
Abstract: In the electric power steering (EPS) system, low-frequency disturbances such as road resistance, irregular mechanical friction, and changing motor parameters can cause steering wheel torque fluctuation and discontinuity. In order to improve the steering wheel torque smoothness, an improved torque control method of an EPS motor is proposed in the paper. A target torque algorithm is established, which is related to steering process parameters such as steering wheel angle and angular speed. Then, a target torque closed-loop control strategy based on the improved ADRC is designed to estimate and compensate the internal and external disturbance of the system, so as to reduce the impact of the disturbance on the steering torque. The simulation results show that the responsiveness and anti-interference ability of the improved ADRC is better than that of the conventional ADRC and PI. The vehicle experiment shows that the proposed control method has good motor current stability, steering torque smoothness, and flexibility when there is low-frequency disturbance.

10 citations

Journal ArticleDOI
Chao Zhang1, Zhipeng Li1, Jie Chen, Qiu Feng1, Shaodan Na1 
TL;DR: In this paper, a non-contact vertical inductive torque sensor was built and investigated, and the effect of different rotors on the nonlinear characteristics of the sensor was analyzed based on the simulation results.

6 citations

Patent
28 Feb 2020
TL;DR: In this paper, a magnetically focused split integrated sensor and a rotating speed, torque and angle calculation method was proposed for measuring and calculating rotating speed and torque of a shaft. But the sensor is not suitable for zero point finding.
Abstract: The invention provides a magnetically-focused split integrated sensor and a rotating speed, torque and angle calculation method, belongs to the technical field of sensors and solves the problem that existing sensors for measuring rotating speed, torque and angle of shafts have high size requirements on the shafts, poor matchability and difficulty in zero point finding. The sensor comprises a to-be-measured shaft and collection mechanisms, two ends of the to-be-measured shaft serve as a shaft input end and a shaft output end respectively, the collection mechanisms are arranged at the shaft input end and the shaft output end respectively, each collection mechanism comprises a rotor circuit board, a receiving coil, a shell and an exciting coil, each rotor circuit board and the corresponding receiving coil are printed on a receiving coil flexible circuit board, and a signal processing circuit is printed on each receiving coil. The sensor is mainly used for measuring and calculating rotating speed, torque and angle of a shaft.

1 citations

Patent
10 Apr 2020
TL;DR: In this article, a measuring system and a measuring method for measuring static torque based on a magnetic focusing mode was described, where a static torque sensor consisting of a rotating shaft, a first magnetic conductance unit and a second magnetic conducting unit is used to measure the moment of the system resistance and other frictional resistances needing to be overcome inthe process.
Abstract: The invention discloses a measuring system and a measuring method for measuring static torque based on a magnetic focusing mode A static torque sensor comprises a rotating shaft, a first magnetic conductance unit and a second magnetic conductance unit The first magnetic conductance unit comprises an excitation device A and a receiving coil A, the excitation device A comprises a magnetic guidingapparatus A and a group of excitation coils A, one end of the rotating shaft is externally sleeved with the receiving coil A, three magnetic guiding apparatuses A are evenly distributed at the outer end of the receiving coil A, a group of excitation coils A is arranged outside each magnetic guiding apparatus A, a housing A-1 and a housing A-2 are arranged outside the three excitation coils A in acovering mode, the housing A-1 and the housing A-2 are used in cooperation to form an annular housing A, and the second magnetic conductance unit and the first magnetic conductance unit are the same in structure When the rotating shaft receives a starting signal, an actual rotating stage is started, and the moment of the system resistance and other frictional resistances needing to be overcome inthe process can be measured by the sensor

Cited by
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Journal ArticleDOI
TL;DR: Rack-force-based steering feel generation logic that creates a familiar steering feel for drivers while transmitting the road condition information is suggested and design criteria of the steering torque feedback controller in the frequency domain are proposed to ensure robust stability, tracking performance and noise attenuation.

4 citations

Journal ArticleDOI
TL;DR: Simulation and experimental results show that, compared with PID cascade Field Oriented Control (PI-FOC), N3C-MPCC can effectively reduce the ripple current of the d-axis and the q-axis, and has a faster current response speed and smooth steering torque.
Abstract: Aiming at the high demand for the torque response speed and torque pulsation of the all-terrain vehicle (ATV) Electric Power Steering (EPS) system, this paper proposes to apply the Model Predictive Current Control to the all-terrain vehicle EPS system. A Novel Three-Vector Model Predictive Current Control (N3V-MPCC) is proposed in this paper to reduce the current ripple and reduce the calculation load. Two effective voltage vectors and a zero vector are selected in the control period through only six times of prediction and application of the Sector Vector Selection method. The duration of each voltage is calculated and output to the Voltage Source Inverter (VSI). Simulation and experimental results show that, compared with PID cascade Field Oriented Control (PI-FOC), N3C-MPCC can effectively reduce the ripple current of the d-axis and the q-axis. In the simulated electric power mode, the q-axis current ripple of the N3V-MPCC is reduced by 66.67%. Experimental results show that the current ripple of the motor is reduced by 60%, and the torque pulsation is reduced by 62.5%. Therefore, N3V-MPCC has a faster current response speed and smooth steering torque.

2 citations

Proceedings ArticleDOI
10 Jul 2020
TL;DR: A comparative analysis of the salp swarm algorithm (SSA) tuned 2-Degree of freedom (DOF) PID controller and the PID controller with a derivative filter (PIDF) in reducing the current consumption of the EPAS system besides in lowering the driving effort is presented.
Abstract: Electric power-assist steering (EPAS) system is an auxiliary system of electric vehicle (EV) that reduces the steering effort of the driver by applying an assist toque using an electric motor to the steering system. This paper aims to present a comparative analysis of the salp swarm algorithm (SSA) tuned 2-Degree of freedom (DOF) PID controller and the PID controller with a derivative filter (PIDF) in reducing the current consumption of the EPAS system besides in lowering the driving effort. Simulation results are discussed to effectively signify the comparison between the two controllers. This study also determines the feasibility of SSA in optimally tuning the controller parameters for the EPAS system.

2 citations

Journal ArticleDOI
01 Nov 2022-Sensors
TL;DR: In this paper , an autoencoder and long short-term memory (LSTM) was used to detect anomalies in electrical power steering (EPS) sensor data, and an anomaly score was calculated based on the reconstruction loss of the output.
Abstract: As anomaly detection for electrical power steering (EPS) systems has been centralized using model- and knowledge-based approaches, EPS system have become complex and more sophisticated, thereby requiring enhanced reliability and safety. Since most current detection methods rely on prior knowledge, it is difficult to identify new or previously unknown anomalies. In this paper, we propose a deep learning approach that consists of a two-stage process using an autoencoder and long short-term memory (LSTM) to detect anomalies in EPS sensor data. First, we train our model on EPS data by employing an autoencoder to extract features and compress them into a latent representation. The compressed features are fed into the LSTM network to capture any correlated dependencies between features, which are then reconstructed as output. An anomaly score is used to detect anomalies based on the reconstruction loss of the output. The effectiveness of our proposed approach is demonstrated by collecting sample data from an experiment using an EPS test jig. The comparison results indicate that our proposed model performs better in detecting anomalies, with an accuracy of 0.99 and a higher area under the receiver operating characteristic curve than other methods providing a valuable tool for anomaly detection in EPS.

2 citations

Journal ArticleDOI
TL;DR: In this article , a series of analyzes considering the traction and steering demands of an autonomous electric vehicle (AEV) as a shuttle is presented, which is dealt with as driving cycle (DC) and driving scenarios (DS) to assess the performance of the AEV.
Abstract: This study presents a series of analyzes considering the traction and steering demands of an autonomous electric vehicle (AEV) as a shuttle. The considered analyzes in here are dealt with as driving cycle (DC) and driving scenarios (DS) to assess the traction and steering performance of the AEV. The aim of this study is to evaluate the issues such as over engineering for AEV traction and steering motor requirements on a certain route by comparatively analyzing traditional and dynamic calculation under the DC and DS. Therefore, DC and DS in the lit-erature are evaluated in terms of different applications, optimization techniques, generation algorithm, parametric characterization, e-motor type etc. Afterwards, NEDC, US06, WLTC, Double Lane Change (DLC), Constant Radius (CR) and Slowly Increase Steer (SIS) are determined. Then, they are arranged according to the vehicle-specific limits on an electric golf car. The modified DCs and DSs are run on the dynamic model of the vehicle. In the performed analysis, the parame-ters such as reference trajectory tracking, yaw angle, tractive and steering forces, lateral and longitudinal displacement-acceleration, steering and traction motor power–speed-torque are investigated. And the obtained results are evaluated by comparing the traditional calculation results.

1 citations