Output Torque Of Motor Research Articles

An application for nonlinear control by input-output linearization technique for pm synchronous motor drive for electric vehicles

This paper leads to present the modified approach of the speed control for permanent magnet synchronous motors applied to electric vehicles using a nonlinear control. The motor's nonlinear dynamics are transformed into a linearized system model using the input-output feedback linearization technique. There are two permanent magnet synchronous motors (PMSM) in the propulsion model. In order to improve the motor's output torque, the direct component of the current is adjusted to zero. The electronic differential, which is used in the calculations, enables each driving wheel to be controlled individually at each curve. The MATLAB/Simulink software is used to implement modeling and simulation in order to assess the effectiveness of the suggested solution. Simulation studies are used to confirm the efficacy of the proposed technique. The obtained results signify that this approach is more accurate.

Simulation of Output Torque of Coal Mine Permanent Magnet DC Motor for Belt Conveyor

With the analysis of the global coal production trend in the past ten years and the requirements of coal mine belt conveyor for drive motor, we summarized the disadvantages of coal mine belt conveyor asynchronous motor such as high loss and low operating efficiency, designed the system structure and simulation calculation model of coal mine permanent magnet DC motor, simulated the output torque of coal mine permanent magnet DC motor for 50N load condition, and realized the output characteristics of coal mine permanent magnet DC motor Calculation.

Nonlinear MPC-Based Acceleration Slip Regulation for Distributed Electric Vehicles

To address the problem in which wheel longitudinal slip rate directly affects the dynamics and handling stability of a vehicle under driving conditions, front and rear dual-motor four-wheel drive electric vehicles (4WD EVs) were selected as the research object in this study. An acceleration slip regulation (ASR) control strategy based on nonlinear model predictive control (NMPC) is proposed. First, the vehicle dynamics model and the Simulink/CarSim co-simulation platform were built. Second, an ASR controller with intervention and exit mechanisms was designed with the control objective of tracking reference speed or optimal slip rate. Then, considering the problem that the left and right wheels could not freely distribute torque under the condition of a split road surface, the motor output torque was determined in accordance with the wheel with the larger slip rate to enhance passibility. Finally, on the basis of the built Simulink/CarSim co-simulation platform, slip rate control simulation experiments were performed on a snow-covered road, a wet asphalt road, a docking road, and a split road. The designed controller can better track target slip rate and it exhibits better dynamic performance and stability than the method with PID control under different road conditions, especially under low speed and low adhesion road conditions, and its robustness can also meet the requirements.

Reliability-Based Robust Design Optimization for Maximizing the Output Torque of Brushless Direct Current (BLDC) Motors Considering Manufacturing Uncertainty

In recent years, the deterministic design optimization method has been widely used to improve the output performance of brushless direct current (BLDC) motors. However, it does not contribute to reducing the failure rate and performance variation of products because it cannot determine the manufacturing uncertainty. In this study, we proposed reliability-based robust design optimization to improve the output torque of a BLDC motor while reducing the failure rate and performance variation. We calculated the output torque and vibration response of the BLDC motor using the electromagnetic–structural coupled analysis. We selected the tooth thickness, slot opening width, slot radius, slot depth, tooth width, magnet thickness, and magnet length as the design variables related to the shape of the stator and rotor that affect the output torque. We considered the distribution of design variables with manufacturing tolerances. We performed a reliability analysis of the BLDC motor considering the distribution of design variables with manufacturing tolerances. Using the reliability analysis results, we performed reliability-based robust design optimization (RBRDO) to maximize the output torque; consequently, the output torque increased by 8.8% compared to the initial BLDC motor, the standard deviation in output performance decreased by 46.9% with improved robustness, and the failure rate decreased by 99.2% with enhanced reliability. The proposed reliability-based robust design optimization is considered to be useful in the actual product design field because it can evaluate both the reliability and robustness of the product and improve its performance in the design stage.

Research on Direct Yaw Moment Control of Electric Vehicles Based on Electrohydraulic Joint Action

To solve the problem of lateral instability of the vehicle caused by insufficient lateral force of the tires due to the insufficient torque provided by the motor to the tire when the vehicle turns sharply or avoids obstacles in an emergency, a layered control method is used to design a lateral stability control system. The upper decision layer selects the yaw rate and the sideslip angle of the center of mass as the control variables and uses the joint state deviation of the yaw rate and the sideslip angle of the center of mass and the rate of change of the deviation as the input of the sliding mode variable structure controller to calculate the additional yaw moment required to maintain vehicle stability. The lower torque distribution layer realizes the distribution of torque through the electro-hydraulic coordinated control method: the torque distribution rule based on real-time load transfer calculates the torque corresponding to the control wheel and generates the torque through the hub motor and transmits it to the wheel. When the torque output from the motor cannot provide sufficient torque for the vehicle, hydraulic braking is used as a compensating control, and the difference between the required yaw torque and the motor-generated yaw torque is used as the required torque for hydraulic control to calculate the wheel cylinder pressure required to brake the wheels. Based on the joint simulation model of MATLAB/Simulink and Carsim, the sine and double shift line working condition are selected for stability simulation experiments. From the simulation results, it can be seen that the yaw rate and sideslip angle of the center of mass of the vehicle with sliding mode control and electro-hydraulic coordinated control almost coincide with the ideal value curve, which are both smaller than the output parameters of the uncontrolled vehicle. From the perspective of the motor output torque, compared with pure motor control, the effect of electro-hydraulic coordinated control is better, and the hydraulic system can compensate for the braking torque in time and enhance the lateral stability of the vehicle. The designed control strategy can make the yaw rate and the sideslip angle of the center of mass of the vehicle follow the reference value better, which can effectively avoid the vehicle sideslip and instability and improve the vehicle yaw stability and driving safety. However, due to the limitations of experimental equipment, the proposed method could not be applied to the real vehicle test. The real vehicle test can better test the control effect of the proposed method.

Optimal Design and Control of a Spoke-Type IPM Motor with Asymmetric Flux Barriers to Improve Torque Density

This paper studies the optimal design and control scheme of a spoke-type interior permanent magnet motor (SIPM). An asymmetric rotor structure with flux barriers is designed to improve the torque density of SIPM. The design method improves the torque density by approximating the maximum value of the magnetic torque and the reluctance torque, wherein the torque components are separated by the frozen permeability method (FPM) to evaluate the contribution. This scheme does not increase the amount of permanent magnets or the motor size, and reduces motor weight while increasing motor torque output. Firstly, the asymmetric flux barriers are applied in a 27/4 SIPM to illustrate the design principle. Further, by optimizing the width of flux barriers, based on finite-element analyze (FEA), a higher torque density is obtained. Compared with the basic model, the output torque and the torque density of the optimal model are both increased. Based on the optimal model, an angle scanning method is proposed to orient the flux vector and dq-axis. Then, the mathematical model of the optimal model is established, and the maximum torque per ampere (MTPA) control system is designed. Compared with the conventional control system, the proposed control system has a higher torque per ampere (TPA), which shows that the designed control system can give full play to the advantages of the high torque density.

Road surface recognition based slip rate and stability control of distributed drive electric vehicles under different conditions

Distributed drive vehicles are prone to wheel slip during driving on low adhesion coefficient roads. Wheel slip will not only cause energy loss, but also the different driving states of the two sides of the wheels will lead to a sharp deterioration in vehicle stability, which will adversely affect the dynamics and safety of the vehicle. For the control characteristics of distributed drive vehicles, a slip rate controller is designed on the basis of slip rate estimation, and a stability control strategy adapted to straight and steering driving are proposed. Firstly, the road surface is identified based on the Burckhardt tire model, and the optimal slip rate of the current road surface is estimated. And the optimal wheel speed corresponding to the current vehicle speed is calculated. An active disturbance rejection controller (ADRC) is established, which controls the four-wheel speeds by adjusting the motor output torque and tracks the optimal wheel speed corresponding to the optimal slip rate. The sliding-mode controller is designed considering the stability requirements of the vehicle during high-speed steering. And the wheel output torque is optimally allocated based on the quadratic programing method. Finally, joint simulations and hardware-in-the-loop tests verify the effectiveness of the control strategy proposed in this paper.

Optimal control of transient processes in marine hybrid propulsion systems: Modeling, optimization and performance enhancement

The voice of energy saving and environmental protection is increasing, and the regulations on energy efficiency of ships are becoming stricter. It has forced the shipping industry to accelerate the development of marine hybrid propulsion systems (MHPS). However, the direct control of power distribution optimized by advanced intelligent algorithms may lead to ship oscillations and speed fluctuations. This paper presents a transient process optimization control strategy for solving multi-energy switching. A MHPS simulation model is established from the first nature principle and experimental data. A simulation analysis of the critical parameters affecting the switching process, namely the clutch operating oil pressure and the permanent-magnet synchronous motor (PMSM) output torque. From the viewpoint of restraining speed and oscillation, a process evaluation function is designed to include speed tracking, shock mitigation, and slip work reduction. An upgraded version of WOA, namely Adaptive Perturbation Quantum wave whale optimization algorithm (APQWOA), is proposed to solve the optimal control problem. This transient process optimization control scheme was tested in real time operation through experiments. The results show that the APQWOA is reliably evaluated, which significantly reduces the speed fluctuation and shock level.

Distributed Drive Electric Bus Handling Stability Control Based on Lyapunov Theory and Sliding Mode Control

To improve the handling stability of distributed drive electric buses, a vehicle stability control system based on direct yaw moment control (DYC) with a hierarchical control structure was designed. Considering that the vehicle dynamics system is highly nonlinear, a nonlinear controller based on Lyapunov stability theory was designed to calculate the required additional yaw moment of the vehicle in the upper controller. In the lower controller, the additional yaw moment is distributed to four wheel-side motors according to the equal proportion torque distribution method, and the direction of wheel-side motor output torque is determined based on the steering state of the vehicle. A co-simulation based on Simulink and Trucksim was conducted to verify the designed controller under two extreme conditions. Simulation results indicate that the proposed method performs feasibly and effectively in the handling stability of vehicles. Compared with traditional sliding mode control (SMC), the proposed control strategy can significantly reduce the chattering of the system, which provides a theoretical basis for the application of this yaw stability control method in engineering practice.

A novel spoke‐type PM motor with asymmetric rotor for low torque pulsation under MTPA control condition

This article presents a novel asymmetric spoke-type rotor structure. It is used to reduce rotor magnetic flux leakage, torque ripple and no-load back-EMF distortion rate while increasing the motor output torque. The traditional method of optimizing torque pulsation is the inverse cosine function, which gives a sinusoidal distribution of the air-gap magnetic field under no-load conditions of the motor. The fundamental wave magnetic field of the air-gap synthetic magnetic field under the load is offset from the no-load air-gap magnetic field. This paper presents the design theory and method of the new type of the asymmetric rotor. Asymmetric spatial harmonics are introduced to the rotor so that the motor has a sinusoidal distribution of the rated load air-gap field under MTPA control. In order to verify the superiority of the new rotor, the performance of four different spoke-type rotor structure motors under the same pole-slot combination was compared. Finally, an experimental prototype is built to verify the theoretical reliability against the design of this paper.

Reinforcement learning control method of torque stability of three-phase permanent magnet synchronous motor

Regarding the control strategy of the permanent magnet synchronous motor, the field-oriented control based on the PI controller have the instability of the output torque. In order to stabilize the output torque of the permanent magnet synchronous motor, this paper adopts reinforcement learning to improve traditional PI controller. Finally, in the MATLAB/Simulink simulation environment, a new control method based on reinforcement learning is established. The simulation results show that the reinforcement learning control method used in this paper can improve the stability of the output torque.

Motor-Temperature-Aware Predictive Energy Management Strategy for Plug-In Hybrid Electric Vehicles Using Rolling Game Optimization

Energy management strategy (EMS) design aims at obtaining excellent fuel economy for plug-in hybrid electric vehicles (PHEVs) through the coordination of multiple energy sources. To reach this goal, a motor needs to start frequently or work for long time. Under these circumstances, the motor temperature inevitably increases and even will trigger motor thermal protection (MTP). Fuel economy and dynamic performance of PHEV would be influenced by such MTP, as it typically reduces the output torque of motor to lower its temperature and prevent it from overheating. Therefore, designing an efficient EMS for PHEVs with the consideration of motor temperature has been a challenging research issue. To solve this problem, this article proposes a predictive EMS using rolling game optimization (RGO) for PHEVs. First, a 2-D Markov chain is designed to predict the future possible velocities, which can provide input information for EMS of PHEVs. Second, the EMS problem in the studied parallel hybrid powertrain is formulated in the model predictive control (MPC) framework, and the motor temperature is added as a key optimization term in the cost function. Third, based on the MPC framework, the min-max game model is established to deal with the worst driving conditions in the future, and the RGO algorithm is proposed to solve this optimization problem. Finally, the comparison work is conducted under three driving cycles and the results show that the proposed strategy improves the fuel economy of the studied PHEV by 20.9% and 11.7% over that using the rule-based (RB) strategy, under the China typical urban driving cycle and real-world driving cycle, respectively. Meanwhile, the proposed strategy effectively limits the motor temperature in a reasonable range.

A 3-DOF Bionic Waist Joint for Humanoid Robot.

In this study, a 3 degree-of-freedom bionic waist joint was developed with coupled tendon-driven mechanism. This bionic waist joint can not only ensure the safety of the human-robot interface, but also increase the load capacity without increasing the weight. The coupled tendon-driven mechanism enables the motion of each joint to be driven by at least two motors together, and enables a maximum torque of 3 times the maximum motor output torque at each joint. The bionic waist joint has similar kinematic characteristics to a human waist, including degrees of freedom (DOF) and range of motion (ROM). The problem of coexistence of coupling and decoupling in the same rotating joint was solved with a novel mechanism that can promote further versatility of the coupled tendon-driven mechanism. The basic movements and characteristics of the waist was validated in the experiment.

Radial Force and Vibration Analysis of Modular Fault‐Tolerant Permanent Magnet Motor with Unequal Span Windings

The low‐speed and high‐torque modular fault‐tolerant permanent magnet motor has the strong fault‐tolerant ability, and can make the motor output torque act on the load directly, and the system has the highest transmission efficiency, which is especially suitable for ship propulsion. In the electric ship direct‐drive propulsion system, the motor is the core of the power system. Because the motor is directly connected with the load, the intermediate buffer mechanism is canceled, so the smooth operation of the motor is put forward to higher requirements. Especially in some fault‐tolerant operations, the unbalanced radial force generated by the asymmetric operation may cause the motor to vibrate greatly, which will reduce the operational life of the motor and even bring new faults. In serious cases, the whole transmission system will be damaged. Therefore, it is necessary to study the vibration of the fault‐tolerant motor under different operating conditions. In this paper, the module combined stator fault‐tolerant permanent magnetic synchronous motor for ship direct‐drive propulsion is taken as the research object. Based on the Maxwell tensor method, the radial force wave expressions of the motor during regular operation and fault‐tolerant operation are derived, and the harmonic order and frequency, which have a significant influence on vibration are summarized. The radial force of the motor under different operating conditions with different control strategies is calculated by the finite element method, and the harmonic components are analyzed by the two‐dimensional Fourier transform. On this basis, the vibration of the motor and the mechanical strength of the rotor support frame are analyzed. The research results of this paper provide some reference for the subsequent vibration reduction strategies of fault‐tolerant motors. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Contact force estimation for serial manipulator based on weighted moving average with variable span and standard Kalman filter with automatic tuning

Sensorless contact force estimation methods facilitate the application of the serial manipulators to manufacturing as they enable robots to interact with unexpected collisions at low cost. In this paper, an external force estimation approach with no embedded sensors is proposed. The approach combines a Weighted Moving Average (WMA) with variable span, the standard Kalman filter (SKF), and its tuning routines. Improved confidence in the motor output torque is achieved due to the reduction of the measurement noise in the motor current by the WMA. The span of the filter adapts continuously to achieve optimal tradeoff between response time and precision of estimation in real time. With the comprehensive information of uncertainty in motor current noise and measurement errors of individual joints speed, an automatic tuning algorithm of the SKF is presented. Validation of the presented estimation approach in terms of estimation accuracy and response time was conducted on the Universal Robot 5 manipulator with differing end effector loads. It was found that the combined force estimation method leads to a reduction of the root-mean-square error and response time by 55.2% and 20.8% in comparison with the established method. The proposed method can be applied to any robotic manipulators as long as the motor information (current, joint position, and joint velocities) is available. Consequently, the cost of collision recognition could be reduced dramatically.

Research on Fuzzy Control Strategy and Genetic Algorithm Optimization for Parallel Hybrid Electric Vehicle

In this paper, the fuzzy control strategy for parallel hybrid electric vehicle(HEV) is proposed. Based on fuzzy logic theory, SOC and torque demand scale factor are taken as the input, a fuzzy logic controller is designed. Combining with the rule-based control strategy(RBCS), the engine and motor output torque are gotten, so the whole energy control strategy is proposed. Then the genetic algorithm(GA) is used to get the optimal results: fuel consumption and emission level, to verify the accuracy of fuzzy control strategy.

Machine Learning for Sensorless Temperature Estimation of a BLDC Motor.

In this article, the authors propose two models for BLDC motor winding temperature estimation using machine learning methods. For the purposes of the research, measurements were made for over 160 h of motor operation, and then, they were preprocessed. The algorithms of linear regression, ElasticNet, stochastic gradient descent regressor, support vector machines, decision trees, and AdaBoost were used for predictive modeling. The ability of the models to generalize was achieved by hyperparameter tuning with the use of cross-validation. The conducted research led to promising results of the winding temperature estimation accuracy. In the case of sensorless temperature prediction (model 1), the mean absolute percentage error MAPE was below 4.5% and the coefficient of determination R2 was above 0.909. In addition, the extension of the model with the temperature measurement on the casing (model 2) allowed reducing the error value to about 1% and increasing R2 to 0.990. The results obtained for the first proposed model show that the overheating protection of the motor can be ensured without direct temperature measurement. In addition, the introduction of a simple casing temperature measurement system allows for an estimation with accuracy suitable for compensating the motor output torque changes related to temperature.

Optimization of speed response of super-high-speed electric air compressor for hydrogen fuel cell vehicle considering the transient current

A super-high-speed electric air compressor for a hydrogen fuel cell vehicle must have a wide speed range and high-speed regulation response capacity. However, due to the distortion of the air gaps magnetic field of the super-high-speed permanent magnet synchronous motor (SHSPMSM) in the super-high-speed domain, the motor's output torque capacity is reduced. Then its speed regulation response capacity is weakened. To solve this problem, firstly, we analyze the effect of transient current on the speed regulation response of the super-high-speed PMSM. Secondly, we proposed a new speed regulation control method, the transient current injection (TCI) control method. Finally, simulation analysis and experimental results demonstrate the effectiveness of the proposed control method. Under target speed of 151,703 rpm, the average electromagnetic torque of SHSPMSM using the TCI control method is increased by 3%. Furthermore, the speed regulation response time decreased by about 0.49s.

Minimum-Nonlinear-Voltage Method for Torque Ripple Suppression in Induction Motor Overmodulation and Field-Weakening Control

The overmodulation-based nonlinear voltage extension could increase the maximum output torque of the induction motor (IM) in the field-weakening (FW) region. Since the voltage distortion increases with the deepening of overmodulation degree, the extreme nonlinear voltage extension (six-step voltage) is only worthwhile in maximum torque demand conditions. However, the conventional overmodulation-FW scheme always adopts the six-step voltage regardless of torque demand, leading to severe torque ripple. To solve this problem, the minimum-nonlinear-voltage (MNV) method is proposed to satisfy the torque demand with minimum overmodulation-voltage nonlinearity. The difference between the limiting and the feedback values of the torque current is used for suppressing the nonlinear voltage extension during a nonmaximum torque demand state. The quantitative relation between the torque ripple and torque demand of the MNV method is calculated and compared with that of the conventional six-step-FW method. Analysis shows that the MNV method can eliminate the torque ripples of low and medium torque demand conditions completely and partially, respectively. The effectiveness of the proposed method is verified experimentally on a 3.7 kW IM platform.

Cooperative control of electrical bicycles

Electric bicycles provide an electric supportive power in addition to the physiological pedalling power of the driver. Electric bicycles thus allow for activities like group rides with people having different degrees of physical fitness. In a group ride, however, each driver would need to adapt the level of electromotive support power (i.e. the assistance level) to the desired level of physiological power output. To overcome this disadvantage, a novel control strategy to automatically adjust the assistance level of the electric bicycle is presented. By this, a uniform velocity can be achieved for all electrical bicycles, while every cyclist applies the amount of power they are most comfortable with. A distributed control approach over a network of electric bicycles is proposed. A reference velocity is calculated by a consensus algorithm. The reference velocity is then used in a local inner feedback loop to adjust the output torque of the support motor. For the velocity feedback loop an H∞-controller is designed. The control algorithms are tested with respect to stability and performance in simulation and experiments. Moreover, local and global stability are established by formal methods.