Vector Control Torque Research Articles

Coordinated torque vectoring and direct yaw control based on Kalman filter control allocation for a four in-wheel electric vehicle

This paper presents a novel hierarchical control architecture designed for a four in-wheel electric vehicle (EV), integrating longitudinal and lateral control strategies to optimize performance and lateral stability. On one hand, a high-level longitudinal controller is synthesized to track a desired speed profile and generate a total torque. On the other hand, a direct yaw control (DYC) strategy is employed for steerability and stability control to generate a yaw moment. To manage the total torque as well as the yaw moment, a control allocation layer is employed. Subsequently, the formulation of the control allocation problem is presented, incorporating a gain-scheduling Daisy chaining Kalman filter (DCKF) control allocation to deal with actuator dynamics and fault tolerance. Results demonstrate enhanced performance in normal and emergency driving. Quick adaptability in case of emergency is achieved without overshooting or undershooting, with a smooth response.

Torque Vectoring Control for Remote-control Driving of Differentialdrive Mobile Robots

Torque Vectoring Control for Remote-control Driving of Differentialdrive Mobile Robots

Torque Vectoring Control as an Energy-Efficient Alternative to Vehicle Suspensions Tuning

Torque Vectoring Control as an Energy-Efficient Alternative to Vehicle Suspensions Tuning

ВПЛИВ ДИСКРЕТНОГО ХАРАКТЕРУ СИГНАЛУ ШВИДКОСТІ НА ПРОЦЕСИ КЕРУВАННЯ МОМЕНТОМ ВЕКТОРНО-КЕРОВАНОГО АСИНХРОННОГО ДВИГУНА

The paper presents the investigation of the impact of the discrete character of the measured by incremental encoder speed signal on the induction motor torque vector control in traction electrical drive. The study is based on mathemati-cal simulations for a direct vector flux-torque control system which provides direct asymptotic field-orientation, asymp-totic flux-torque trajectory tracking, and asymptotic decoupling of the torque and flux subsystems. The parameters of the induction motor and encoder used in the study correlate with used in the real traction electromechanical systems of trolleybuses. It is shown that introduction of first order filter in the speed measurement channel reduces the induction motor’s current and torque spikes, but leads to an error in torque control and degradation of the rotor flux field-orientation conditions. Combined utilization of filtered and unfiltered speed signal is proposed in order to avoid this disadvantage. Ref. 7, fig. 6.

Comparison of incremental encoder digital signal processing techniques for theinduction motor flux-torque vector control systems

The articlepresents the results of a study on the effectiveness of varioustechniques forsynchronous reference frame angular position numerical calculation in flux-torque vector control system of induction motor.Investigation was caried out taking into account the discrete nature of the angular speedsignal obtained using an incremental encoder. In this workfor investigation by simulation useda direct torque vector control system, which, in the presence of an ideal rotor angular speedsignal, ensures direct asymptotic field orientation, asymptotic tracking of torque-flux referencetrajectories, as well as asymptotic decouplingtorque and flux subsystems. The parameters of the inductionmotor and encoder used in the study correspond to those existing in traction electromechanical systems of city trolleybuses. It is shown that the discrete nature of the angular speedsignal, which usedin synchronous reference frameposition equation of flux-torque vector control systems, introduces field orientation errors and leads to current and torque ripples, which in a real system increase acoustic noise and can cause mechanical vibrations and resonance phenomena. An analysis of possible ways to reduce the influence of the speed signal discreteness on flux-torque control is performed, and a method for practical implementation of the synchronous reference frame angular position numerical calculationis proposed. This method allows ensuring conditions for more precisefield orientation and, by using an additional filter for the angular speedsignal, reducing the level of current and torque ripplesto negligibly small values without affecting the field orientation processes. The proposed solution can be used in the development of high dynamicflux-torque vector control systems for inductionmotors using incremental encoders, including for electric vehicles.

Wheel Torque Distribution Control Strategy for Electric Vehicles Dynamic Performance With an Electric Torque Vectoring Drive Axle

The ability of active chassis control for dynamic performance improvement of electric vehicles with centralized drive system is limited duo to the driving torque between two-side wheels always equally distributed. To solve this problem, this paper proposes a novel electric torque vectoring (TV) drive-axle and its torque distribution control strategy, which can realize the function of arbitrary distribution of the left/right wheel driving torque in the form of centralized drive, thereby improving the dynamic performance of the vehicle. First, the structure and torque distribution principle of TV drive-axle are analyzed theoretically. Subsequently, an accurate mathematical model of TV drive-axle is established based on bond graph theory. Next, a wheel torque distribution control strategy of TV drive-axle is proposed based on hierarchical control approach to improve the vehicle’s handling stability. Wherein, the target yaw rate motion tracking controller as the upper-level controller is designed based on the second-order super-twist sliding mode control (SS-SMC) algorithm, and the wheel drive anti-slip controller in lower-level is used to restrict possible wheels slipping. Finally, the off-line simulation and hardware-in-the-loop (HIL) experiment results suggest that the proposed novel TV drive-axle and control strategy can significantly improve the handling stability and steering flexibility of the vehicle.

On Torque Vectoring Control: Review and Comparison of State-of-the-Art Approaches

Torque vectoring is a widely known technique to improve vehicle handling and to increase stability in limit conditions. With the advent of electric vehicles, this is becoming a key topic since it is possible to have distributed powertrains, i.e., multiple motors are adopted, in which each motor is controlled separately from the others. Moreover, electric motors deliver the torque required by the controller faster and more precisely than internal combustion engines, active differentials and conventional hydraulic brakes. The state of the art of Direct Yaw Moment Control (DYC) techniques, ranging from classical to modern control theories, are analyzed and discussed in this paper. The aim is to give an overview of the currently available approaches while identifying their drawbacks regarding performances and robustness when dealing with common issues like model uncertainties, external disturbances, friction limit and common state estimation problems. This contribution analyzes all the steps from the lateral dynamics reference generation to the desired control action computation and allocation to the available actuators. In addition, some of the presented control logic is evaluated in a simulation environment for a passenger car. Results of both open-loop and closed-loop maneuvers allow the comparison and clarification of each control strategy’s key advantages.

Improving the operational characteristics of electrical power systems of marine vessels

THE PURPOSE. Consider the experience of use and conduct a study of the electrical power systems of sea vessels to determine the possibility of improving their operational characteristics. Obtain data on noise and vibration levels of electrical power systems elements.METHODS. The article analyzes the electrical power systems of the Azipod type steering columns of the Baltika icebreaker. The issue of regulating the rotation speed of propulsion electric motors using frequency control based on a DC link and parallel-connected inverter units on IGBT transistors is considered. Motor control on the frequency converter side can be based on direct torque control, scalar and vector control. There are control modes for reducing and increasing voltage.RESULTS. Typical dependences of structure-borne noise levels of main engines and generators are given. Measurements were taken at various frequencies of engine sound power levels, exhaust gases and vibration of generator sets. Experimental oscillograms of studies of the parallel operation of diesel generator sets were obtained, on which power exchange and common-mode oscillations were recorded.CONCLUSION. It is proposed to use multiphase AC electric motors to improve performance characteristics, including reducing noise and vibration. The existing experience in using frequency converters based on a rectifier section and inverter units in electric rowing installations with Azipod propellers makes it possible to implement such a change. To do this, it is necessary to parallelize the inverters that supply each of the three phases and provide the appropriate phase shifts.

Integrated Torque Vectoring Control Using Vehicle Yaw Rate and Sideslip Angle for Improving Steering and Stability of All Off-Wheel-Motor Drive Electric Vehicles

Integrated Torque Vectoring Control Using Vehicle Yaw Rate and Sideslip Angle for Improving Steering and Stability of All Off-Wheel-Motor Drive Electric Vehicles

An Energy-Oriented Torque-Vector Control Framework for Distributed Drive Electric Vehicles

The over-actuated characteristics of distributed drive electric vehicles (DDEVs) provide a flexible platform to pursue higher holistic performance. This paper proposes a dual-model predictive control (MPC)-based hierarchical framework to realize the energy saving while improving the handling stability for DDEVs. The upper layer allocates the torque vector through the front/rear axles, which can provide a high-efficiency zone for the in-wheel motors and reduce the energy consumption. The lower layer generates a direct-yaw-moment control input by differential longitudinal forces of the left/right wheels to ensure the vehicle handling stability. Considering the time-varying state variables, a linear-time-varying model-predictive-control (LTV-MPC) method is adopted to guarantee the accuracy of the model. The combined magic formula tire model is used to modify the tire parameters, including tire longitudinal stiffness and cornering stiffness. The soft constraint constructed by β-γ phase plane is introduced in the LTV-MPC to ensure the vehicle stability, based on which, a relaxation factor is designed to reduce the energy consumption due to the excessive direct-yaw-moment control inputs. The simulation and hardware-in-the-loop (HIL) test results show that the proposed control framework can effectively reduce the energy consumption for DDEVs while ensuring the vehicle handling stability.

Torque Vectoring Control Strategies Comparison for Hybrid Vehicles with Two Rear Electric Motors

In today’s automotive industry, electrification is a major trend. In-wheel electric motors are among the most promising technologies yet to be fully developed. Indeed, the presence of multiple in-wheel motors acting as independent actuators allows for the implementation of innovative active systems and control strategies. This paper analyzes different design possibilities for a torque vectoring system applied to an originally compact front-wheel drive hybrid electric vehicle with one internal combustion engine for the front axle and two added electric motors integrated in the wheels of the rear axle. A 14 degrees of freedom vehicle model is present o accurately reproduce the nonlinearities of vehicle dynamic phenomena and exploited to obtain high-fidelity numerical simulation results. Different control methods are compared, a PID, an LQR, and four different sliding mode control strategies. All controllers achieve sufficiently good results in terms of lateral dynamics compared with the basic hybrid version. The various aspects and features of the different strategies are analyzed and discussed. Chattering reduction strategies are developed to improve the performance of sliding mode controllers. For a complete overview, control systems are compared using a performance factor that weighs control accuracy and effort in different driving maneuvers, i.e., ramp and step steering maneuvers performed under quite different conditions ranging up to the limits.

Unified Vector Torque Control for Reluctance Motor With Different Coil Pitch

This paper unifies the vector torque control of reluctance motor with different coil pitch in the classic vector model frameworks, including the typical switched reluctance motor (SRM), mutually coupled switched reluctance motor (MCSRM), synchronous reluctance motor (SynRM) and so on. Based on the proposed vector model, the instantaneous electromagnetic torque of the reluctance motor is decoupled into two components. The first partial torque is called as the Synchronous-Speed Reluctance Force (SSRF), generated by the interaction of the <i>d</i>-axis and <i>q</i>-axis currents. The second partial torque is the Double-Speed Reluctance Force (DSRF), generated by the interaction between the <i>dq</i>-plane current and the 0-axis current. The torque formula can reflect the torque generation and fluctuation reasons, and the proportion of the two torque components is related to the ratio of the varying components of the motor&#x0027;s self-inductance and mutual inductance. Different types of reluctance motors can be summarized in the unified vector model. The conclusion is that the SynRM only contains the SSRF torque while the typical SRM and MCSRM contain both the SSRF torque and DSRF torque. The proposed unified vector torque control method is verified by simulations and experiments of 12-slot 8-pole reluctance motors with different coil pitch.

Analysis of the Efficiency of Traction Drive Control Systems of Electric Locomotives with Asynchronous Traction Motors

An analysis of the operating conditions of the traction drives of an electric rolling stock with asynchronous traction motors was conducted. In the process of operation, the electric traction drive with both direct torque control and vector control was found to possibly experience unstable modes, both in terms of power supply and load. The models of electric locomotive traction drives with asynchronous electric motors with either vector or direct torque control were adapted to account for the possible presence of the aforementioned operational factors. As a result of the modeling, the starting characteristics of the electric traction drives with different control systems were obtained both in the absence and in the presence of power supply and load disturbances. The following cases were investigated for the drive with vector and direct torque control in the absence of power supply and torque disturbances: drive output at the rated speed of rotation of the electric motor shaft; 10% reduction in the rated speed; 10% increase in the rated speed. The comparison of the results obtained has demonstrated that, at lower than nominal frequencies, the electric traction drive with direct torque control has higher accuracy in its regulation of the rotational speed and torque, lower power consumption from the power supply, lower torque overshooting, but a higher level of torque pulsations than the electric traction drive with vector control. Meanwhile, at higher than nominal frequencies, the vector control has higher accuracy in its regulation of the speed, lower torque overshooting, shorter duration of transient processes, and lower torque pulsations than the direct torque control. Moreover, as a result of the investigations, the traction drive with direct torque control has been found to be more resistant to power supply and load disturbances. The results of this work are applicable to the investigation of the influence of electric traction drive control methods on the energy efficiency of the traction drive of an electric locomotive with an alternating current (AC).

Deep Reinforcement Learning-Based Torque Vectoring Control Considering Economy and Safety

This paper presents a novel torque vectoring control (TVC) method for four in-wheel-motor independent-drive electric vehicles that considers both energy-saving and safety performance using deep reinforcement learning (RL). Firstly, the tire model is identified using the Fibonacci tree optimization algorithm, and a hierarchical torque vectoring control scheme is designed based on a nonlinear seven-degree-of-freedom vehicle model. This control structure comprises an active safety control layer and a torque allocation layer based on RL. The active safety control layer provides a torque reference for the torque allocation layer to allocate torque while considering both energy-saving and safety performance. Specifically, a new heuristic random ensembled double Q-learning RL algorithm is proposed to calculate the optimal torque allocation for all driving conditions. Finally, numerical experiments are conducted under different driving conditions to validate the effectiveness of the proposed TVC method. Through comparative studies, we emphasize that the novel TVC method outperforms many existing related control results in improving vehicle safety and energy savings, as well as reducing driver workload.

Investigation of Vehicle Stability by Integration of Active Suspension, Torque Vectoring, and Direct Yaw Control

Investigation of Vehicle Stability by Integration of Active Suspension, Torque Vectoring, and Direct Yaw Control

Decentralized integration of constrained active steering and torque vectoring systems to energy-efficient stability control of electric vehicles

In this paper, the optimal driving torques of four wheels in an electric vehicle (EV) are obtained by minimizing the losses of four in-wheel motors. In order to slightly change these optimal torques for vehicle stability recovery, a new constrained active front steering (AFS) system is analytically designed and integrated with the torque vectoring (TV) system in a novel decentralized structure. In the proposed structure, the required external yaw moment is applied by the TV controller only when the constrained AFS is filled to capacity determined by a stability index extracted from the nonlinear phase plane analysis. As a result of this integration strategy, the external yaw moment is used as low as possible. Consequently, the torques in electrical motors are used near the optimal values consistent with optimal energy consumption. Comparative simulation studies with the standalone TV are conducted in the CarSim software environment to show the efficiency of the proposed decentralized control structure in terms of energy consumption and stability. Moreover, the suitability of the constrained control method used in the integration structure is shown in comparison with the well-known nonlinear model predictive control method in terms of practical implementation.

A Real-Time NMPC Strategy for Electric Vehicle Stability Improvement Combining Torque Vectoring With Rear-Wheel Steering

On low-friction surfaces, vehicle stability is significantly influenced by nonlinear vehicle dynamics. To realize stability improvement, a real-time nonlinear model predictive control (NMPC) strategy that combines torque vectoring control (TVC) and rear-wheel steering (RWS) is proposed. A multitarget optimization objective function that considers system state tracking, stability, control constraints, and actuation energy consumption is established. Then, a fast-solving algorithm based on Pontryagin’s minimum principle (PMP) is proposed to reduce the heavy computational burden of NMPC and satisfy the real-time computation requirement of vehicular applications. The effectiveness of the proposed fast-solving algorithm is verified by comparing its closed-loop performance with interior point optimization (IPOPT). A series of hardware-in-the-loop (HIL) experiments with the real human driver is conducted to verify the effectiveness of the proposed fast-solving algorithm and combined control strategy. Furthermore, the HIL results show that the proposed combined control strategy can improve a vehicle’s handling stability on a low-friction surface and has a better performance and lower actuation energy consumption than the TVC-only method.

On nonlinear model predictive direct yaw moment control for trailer sway mitigation

In car–trailer combinations, the hitch angle is the relative yaw angle between towing car and trailer. The literature has shown that the inclusion of the hitch angle measurement for the feedback control of trailer oscillations can bring safety benefits, compared with conventional trailer sway mitigation algorithms based on the yaw rate of the car. Given the nonlinearity of the vehicle system in the typical conditions requiring the hitch angle control function intervention, nonlinear model-based controllers could be an effective solution. This paper presents four real-time implementable nonlinear model predictive control (NMPC) formulations, using the hitch angle measurement for the torque-vectoring (TV) control of an electric front-wheel drive car towing a trailer. The simulation results show that: (i) the active safety is enhanced by the proposed NMPC TV formulations, with respect to a benchmarking NMPC TV controller only based on the control of the towing car; (ii) the NMPC formulations that directly constrain the hitch angle error, or perform continuous hitch angle tracking, outperform those that modify the reference yaw rate or yaw rate error based on the hitch angle error; and (iii) the NMPC approaches including a dynamic model of the trailer are robust with respect to variations of trailer parameters.

Torque Distribution Algorithm for Four In-wheel Motors Drive Electric Vehicle Based on Torque Vector Control

Torque distribution algorithm, including the calculation of additional yaw moment and the distribution of four in-wheel motors torque, is studied. An additional yaw moment controller based on the MPC is designed. The predictive model is constructed based on 2-DOF vehicle model. The optimal additional yaw moment is obtained by solving the equivalent quadratic programming problem, which considers the constraints of target yaw rate, CG sideslip angle and minimum variation of additional yaw moment.Wheel torque distribution based on the optimal tire adhesion coefficient is established to realize additional yaw moment. Combined with the constraints of front and rear axle driving force, additional yaw moment and tire friction circle, the optimal wheel force distribution problem is transformed into a quadratic programming problem. In the special conditions such as lateral force saturation and driving anti-skid function trigger, the constraints are relaxed to avoid the equation without feasible solution.The simulation results of transient steering test, steady state steering test and extreme steering test showed that the application of the algorithm can shorten the response time of yaw rate, improve the cornering behavior of the vehicle under large lateral acceleration, and reduce the maximum passing speed under in slalom test to improve the handling and stability of the vehicle.

Optimal Speed–Torque Control of Asynchronous Motor for Electric Cars in the Field-Weakening Region Based on Voltage Vector Optimization

In this article, model predictive (MP) and deep belief net (DBN) are introduced to optimize and predict the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis stator voltage of asynchronous motors for electric cars in the field-weakening region to achieve the optimal “speed–torque” (represents the optimization of speed and torque performance) control. First, the analytical model of the maximum torque output is established, and the effect of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis voltage on the torque output is analyzed. Second, to reduce the influence of proportional–integral parameter tuning, optimize the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis voltage, and achieve the accurate torque control, MP is introduced to establish an analytical model of MP controller tracking current loop for generating the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> -axis voltage. Third, the maximum torque vector control system based on the MP controller is built, and the influence of system parameters on control effect is analyzed. Fourth, the simulation data are collected, and the DBN voltage prediction model is established. The model is embedded in the field-oriented control to achieve optimal “speed–torque” control. Finally, the dynamometer experimental platform is established to collect the experimental data and establish the DBN voltage prediction model. The validity of the method is verified through the voltage data calibration, “speed–torque” characteristic calibration, motor efficiency calibration, “speed–torque” response, and ripple test.