Electrically controllable spin filtering in zigzag phosphorene nanoribbon based normal–antiferromagnet–normal junctions

We investigated the electric controllable spin-filtering effect in a zigzag phosphorene nanoribbon(ZPNR) based normal–antiferromagnet–normal junction. Two ferromagnets are closely coupled to the edges of the nanoribbon and form the edge-to-edge antiferromagnetism. Under an in-plane electric field, the two degenerate edge bands of the edge-to-edge antiferromagnet split into four spin-polarized sub-bands and a 100% spin-polarized current can be easily induced with the maximal conductance 2e~2/h. The spin polarization changes with the strength of the electric field and the exchange field,and changes sign at opposite electric fields. The spin-polarized current switches from one edge to the other by reversing the direction of the electric field. The edge current can also be controlled spatially by changing the electric potential of the scattering region. The manipulation of edge current is useful in spin-transfer-torque magnetic random-access memory and provides a practical way to develop controllable spintronic devices.

Adaptive Robust Servo Control for Vertical Electric Stabilization System of Tank and Experimental Validation

A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.

Coordinated Voltage Control of Distribution Network ConsideringMultiple Types of Electric Vehicles

The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.

Stochastic sampled-data multi-objective control of active suspension systems for in-wheel motor driven electric vehicles

This paper addresses the sampled-data multi-objective active suspension control problem for an in-wheel motor driven electric vehicle subject to stochastic sampling periods and asynchronous premise variables.The focus is placed on the scenario that the dynamical state of the half-vehicle active suspension system is transmitted over an in-vehicle controller area network that only permits the transmission of sampled data packets.For this purpose,a stochastic sampling mechanism is developed such that the sampling periods can randomly switch among different values with certain mathematical probabilities.Then,an asynchronous fuzzy sampled-data controller,featuring distinct premise variables from the active suspension system,is constructed to eliminate the stringent requirement that the sampled-data controller has to share the same grades of membership.Furthermore,novel criteria for both stability analysis and controller design are derived in order to guarantee that the resultant closed-loop active suspension system is stochastically stable with simultaneous𝐻2 and𝐻∞performance requirements.Finally,the effectiveness of the proposed stochastic sampled-data multi-objective control method is verified via several numerical cases studies in both time domain and frequency domain under various road disturbance profiles.

Implementation of Fuzzy Logic Control into an Equivalent Minimization Strategy for Adaptive Energy Management of A Parallel Hybrid Electric Vehicle

As government agencies continue to tighten emissions regulations due to the continued increase in greenhouse gas production, automotive industries are seeking to produce increasingly efficient vehicle technology. Hybrid electric vehicles (HEVs) have been introduced to mitigate problems while improving fuel economy. HEVs have led to the demand of creating more advanced controls software to consider multiple components for propulsive power in a vehicle. A large section in the software development process is the implementation of an optimal energy management strategy meant to improve the overall fuel efficiency of the vehicle. Optimal strategies can be implemented when driving conditions are known a prior. The Equivalent Consumption Minimization Strategy (ECMS) is an optimal control strategy that uses an equivalence factor to equate electrical to mechanical power when performing torque split determination between the internal combustion engine and electric motor for propulsive and regenerative torque. This equivalence factor is determined from offline vehicle simulations using a sensitivity analysis to provide optimal fuel economy results while maintaining predetermined high voltage battery state of charge (SOC) constraints. When the control hierarchy is modified or different driving styles are applied, the analysis must be redone to update the equivalence factor. The goal of this work is to implement a fuzzy logic controller that dynamically updates the equivalence factor to improve fuel economy, maintain a strict charge sustaining window of operation for the high voltage battery, and reduce computational time required during algorithm development. The adaptive algorithm is validated against global optimum fuel economy and charge sustaining results from a sensitivity analysis performed for multiple drive cycles. Results show a maximum fuel economy improvement of 9.82% when using a mild driving style and a 95% success rate when maintaining an ending SOC within 5% of the desired SOC regardless of starting SOC.

Research on Electrical Automation Control Design Based on PLC Technology

As science and technology continue to progress forward,electrical automation engineering is also developing,of which programmable logic controller(PLC)technology is widely being used.Through the integration of PLC technology and traditional electrical automation technology,good development of modern science and technology is promoted while traditional automation is preserved.The development of electrical engineering can greatly improve the strength of science,technology,and economy in our country.Based on PLC technology,this paper analyzes the design of electrical automation control.

Fault tolerant control of electric pitch control system based on single current detection

In view of the current sensors failure in electric pitch system,a variable universe fuzzy fault tolerant control method of electric pitch control system based on single current detection is proposed.When there is single or two-current sensor fault occurs,based on the proposed method the missing current information can be reconstructed by using direct current（DC）bus current sensor and the three-phase current can be updated in time within any two adjacent sampling periods,so as to ensure stability of the closed-loop system.And then the switchover and fault tolerant control of fault current sensor would be accomplished by fault diagnosis method based on adaptive threshold judgment.For the reconstructed signal error caused by the modulation method and the main control target of electric pitch system,a variable universe fuzzy control method is used in the speed loop,which can improve the anti-disturbance ability to load variation,and the robustness of fault tolerance system.The results show that the fault tolerant control method makes the variable pitch control system still has ideal control characteristics in case of sensor failure although part of the system performance is lost,thus the correctness of the proposed method is verified.

Driving and Braking Control of PM Synchronous Motor Based on Low-resolution Hall Sensor for Battery Electric Vehicle

Resolvers are normally employed for rotor positioning in motors for electric vehicles, but resolvers are expensive and vulnerable to vibrations. Hall sensors have the advantages of low cost and high reliability, but the positioning accuracy is low. Motors with Hall sensors are typically controlled by six-step commutation algorithm, which brings high torque ripple. This paper studies the high-performance driving and braking control of the in-wheel permanent magnetic synchronous motor （PMSM） based on low-resolution Hall sensors. Field oriented control （FOC） based on Hall-effect sensors is developed to reduce the torque ripple. The positioning accuracy of the Hall sensors is improved by interpolation between two consecutive Hall signals using the estimated motor speed. The position error from the misalignment of the Hall sensors is compensated by the precise calibration of Hall transition timing. The braking control algorithms based on six-step commutation and FOC are studied. Two variants of the six-step commutation braking control, namely, half-bridge commutation and full-bridge commutation, are discussed and compared, which shows that the full-bridge commutation could better explore the potential of the back electro-motive forces （EMF）, thus can deliver higher efficiency and smaller current ripple. The FOC braking is analyzed with the phasor diagrams. At a given motor speed, the motor turns from the regenerative braking mode into the plug braking mode if the braking torque exceeds a certain limit, which is proportional to the motor speed. Tests in the dynamometer show that a smooth control could be realized by FOC driving control and the highest efficiency and the smallest current ripple could be achieved by FOC braking control, compared to six-step commutation braking control. Therefore, FOC braking is selected as the braking control algorithm for electric vehicles. The proposed research ensures a good motor control performance while maintaining low cost and high reliability.

Control Algorithm of Electric Vehicle in Coasting Mode Based on Driving Feeling

Coasting in gear is a common driving mode for the conventional vehicle equipped with the internal combustion engine（ICE）, and the assistant braking function of ICE is utilized to decelerate the vehicle in this mode. However, the electric vehicle（EV） does not have this feature in the coasting mode due to the relatively small inertia of the driving motor, so it will cause the driver cannot obtain the similar driving feeling to that of the conventional vehicle, and even a traffic accident may occur if the driver cannot immediately adapt to the changes. In this paper, the coasting control for EV is researched based on the driving feeling. A conventional vehicle equipped with continuously variable transmission（CVT） is taken as the reference vehicle, and the combined simulation model of EV is established based on AVL CRUISE and MATLAB/Simulink. The torque characteristic of the CVT output shaft is measured in coasting mode, and the data are smoothed and fitted to a polynomial curve. For the EV in coasting mode, if the state of charge（SOC） of the battery is below 95%, the polynomial curve is used as the control target for the torque characteristic of the driving motor, otherwise, the required torque is replaced by hydraulic braking torque to keep the same deceleration. The co-simulation of Matlab/Simulink/Stateflow and AVL CRUISE, as well as the hardware-in-loop experiment combined with d SPACE are carried out to verify the effectiveness and the real-time performance of the control algorithm. The results show that the EV with coasting braking control system has similar driving feeling to that of the reference vehicle, meanwhile, the battery SOC can be increased by 0.036% and 0.021% in the initial speed of 100 km/h and 50 km/h, respectively. The proposed control algorithm for EV is beneficial to improve the driving feeling in coasting mode, and it also makes the EV has the assistant braking function.

Decentralized Dynamic Event-Triggered Communication and Active Suspension Control of In-Wheel Motor Driven Electric Vehicles with Dynamic Damping

This paper addresses the co-design problem of decentralized dynamic event-triggered communication and active suspension control for an in-wheel motor driven electric vehicle equipped with a dynamic damper. The main objective is to simultaneously improve the desired suspension performance caused by various road disturbances and alleviate the network resource utilization for the concerned in-vehicle networked suspension system. First, a T-S fuzzy active suspension model of an electric vehicle under dynamic damping is established. Second,a novel decentralized dynamic event-triggered communication mechanism is developed to regulate each sensor's data transmissions such that sampled data packets on each sensor are scheduled in an independent manner. In contrast to the traditional static triggering mechanisms, a key feature of the proposed mechanism is that the threshold parameter in the event trigger is adjusted adaptively over time to reduce the network resources occupancy. Third, co-design criteria for the desired event-triggered fuzzy controller and dynamic triggering mechanisms are derived. Finally, comprehensive comparative simulation studies of a 3-degrees-of-freedom quarter suspension model are provided under both bump road disturbance and ISO-2631 classified random road disturbance to validate the effectiveness of the proposed co-design approach. It is shown that ride comfort can be greatly improved in either road disturbance case and the suspension deflection, dynamic tyre load and actuator control input are all kept below the prescribed maximum allowable limits, while simultaneously maintaining desirable communication efficiency.

Aircraft Electric Anti-skid Braking System Based on Fuzzy-PID Controller with Parameter Self-adjustment Feature

The principle of electric braking system is analyzed and an anti-skid braking system based on the slip rate control is proposed.The fuzzy-PID controller with parameter self-adjustment feature is designed for the anti-skid braking system.The dynamic model of aircraft ground braking is established in the simulation environment of MATLAB/SIMULINK,and simulation results of dry runway and wet runway are presented.The results show that the fuzzy-PID controller with parameter self-adjustment feature for the electric anti-skid braking system keeps working in the state of stability and the brake efficiencies are increased to 93%on dry runway and 82%on wet runway respectively.

Direct Yaw Moment Control for Distributed Drive Electric Vehicle Handling Performance Improvement

For a distributed drive electric vehicle（DDEV） driven by four in-wheel motors, advanced vehicle dynamic control methods can be realized easily because motors can be controlled independently, quickly and precisely. And direct yaw-moment control（DYC） has been widely studied and applied to vehicle stability control. Good vehicle handling performance： quick yaw rate transient response, small overshoot, high steady yaw rate gain, etc, is required by drivers under normal conditions, which is less concerned, however. Based on the hierarchical control methodology, a novel control system using direct yaw moment control for improving handling performance of a distributed drive electric vehicle especially under normal driving conditions has been proposed. The upper-loop control system consists of two parts： a state feedback controller, which aims to realize the ideal transient response of yaw rate, with a vehicle sideslip angle observer; and a steering wheel angle feedforward controller designed to achieve a desired yaw rate steady gain. Under the restriction of the effect of poles and zeros in the closed-loop transfer function on the system response and the capacity of in-wheel motors, the integrated time and absolute error（ITAE） function is utilized as the cost function in the optimal control to calculate the ideal eigen frequency and damper coefficient of the system and obtain optimal feedback matrix and feedforward matrix. Simulations and experiments with a DDEV under multiple maneuvers are carried out and show the effectiveness of the proposed method： yaw rate rising time is reduced, steady yaw rate gain is increased, vehicle steering characteristic is close to neutral steer and drivers burdens are also reduced. The control system improves vehicle handling performance under normal conditions in both transient and steady response. State feedback control instead of model following control is introduced in the control system so that the sense of control intervention to drivers is relieved.

A Simplified Sliding Mode Controlled Electronic Differential for an Electric Vehicle with Two Independent Wheel Drives

This paper presents a simple sliding mode control strategy used for an electronic differential system for electric vehicle with two independent wheel drives. When a vehicle drives along a curved road lane, the speed of the inner wheel has to be different from that of the outer wheel in order to prevent the vehicle from vibrating and travelling an unsteady path. Because each wheel of this electrical vehicle has independent driving force, an electrical differential system is required to replace a gear differential system. However, it is difficult to analyse the nonlinear behaviour of the differential system in relation to the speed and steering angle, as well as vehicle structure. The proposed propulsion system consists of two permanent magnet synchronous machines that ensure the drive of the two back driving wheels. The proposed control structure called independent machines for speed control allows the achievement of an electronic differential which ensures the control of the vehicle behaviour on the road. It also allows to control, independently, every driving wheel to turn at different speeds in any curve. Analysis and simulation results of the proposed system are presented in this paper.

Four Wheel Independent Drive Electric Vehicle Lateral Stability Control Strategy

In this paper,a kind of lateral stability control strategy is put forward about the four wheel independent drive electric vehicle.The design of control system adopts hierarchical structure.Unlike the previous control strategy,this paper introduces a method which is the combination of sliding mode control and optimal allocation algorithm.According to the driver’s operation commands(steering angle and speed),the steady state responses of the sideslip angle and yaw rate are obtained.Based on this,the reference model is built.Upper controller adopts the sliding mode control principle to obtain the desired yawing moment demand.Lower controller is designed to satisfy the desired yawing moment demand by optimal allocation of the tire longitudinal forces.Firstly,the optimization goal is built to minimize the actuator cost.Secondly,the weighted least-square method is used to design the tire longitudinal forces optimization distribution strategy under the constraint conditions of actuator and the friction oval.Beyond that,when the optimal allocation algorithm is not applied,a method of axial load ratio distribution is adopted.Finally,Car Sim associated with Simulink simulation experiments are designed under the conditions of different velocities and different pavements.The simulation results show that the control strategy designed in this paper has a good following effect comparing with the reference model and the sideslip angle is controlled within a small rang at the same time.Beyond that,based on the optimal distribution mode,the electromagnetic torque phase of each wheel can follow the trend of the vertical force of the tire,which shows the effectiveness of the optimal distribution algorithm.

H∞ control of novel active steering integrated with electric power steering function

Based on the traditional active steering system, a novel active steering system integrated with electric power steering function was introduced, which can achieve the functions of both active steering and electric power steering. In view of the interference from road random signal and sensor noise in the novel active steering system, the H∞ control model of the novel active steering system was built. With satisfying steering feel, good robust performance and steering stability being the control objectives, the H∞ controller for the novel active front steering (AFS) system was designed. The simulation results show that the novel AFS system with H∞ control strategy can attenuate the road interference quickly, and there is no resonance peak in the bode diagram. It can make the driver obtain more useful information in the low frequency range, and attenuate the road interference better in the high frequency range, thus the driver can get more satisfying road feeling. Therefore, the designed H∞ controller can synthesize the advantages of both robust performance and robust stability, and has certain contribution to the design of novel AFS system.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

Controller Design for Electric Power Steering System Using T-S Fuzzy Model Approach

Pressure ripples in electric power steering （EPS） systems can be caused by the phase lag between the driver s steering torque and steer angle, the nonlinear frictions, and the disturbances from road and sensor noise especially during high-frequency maneuvers. This paper investigates the use of the robust fuzzy control method for actively reducing pressure ripples for EPS systems. Remarkable progress on steering maneuverability is achieved. The EPS dynamics is described with an eight-order nonlinear state-space model and approximated by a Takagi-Sugeno （T-S） fuzzy model with time-varying delays and external disturbances. A stabilization approach is then presented for nonlinear time-delay systems through fuzzy state feedback controller in parallel distributed compensation （PDC） structure. The closed-loop stability conditions of EPS system with the fuzzy controller are parameterized in terms of the linear matrix inequality （LMI） problem. Simulations and experiments using the proposed robust fuzzy controller and traditional PID controller have been carried out for EPS systems. Both the simulation and experiment results show that the proposed fuzzy controller can reduce the torque ripples and allow us to have a good steering feeling and stable driving.

An Investigation into Regenerative Braking Control Strategy for Hybrid Electric Vehicle

Energy regeneration during braking is an important technique for hybrid electric vehicle (HEV) to improve their fuel economy and extend their driving range. Due to the effect of regenerative braking torque which is added by electric motor, the braking torque distribution between front and rear axles should be changed and the control logic of anti-lock braking system (ABS) ought to be adjusted according to the regenerative braking torque. This paper put forward a braking control strategy for hybrid electric vehicle; the control strategy is implemented with eight DOFs (Degree-of-Freedom) nonlinear vehicle forward simulation model which is built under the environment of Matlab/Simulink. Based on target wheel slip ratio, a fuzzy logic approach was applied to maintain the optimal target slip ratio so that best compromise between hydraulic torque and regenerative torque can be obtained for the vehicle.

Energy Control of Plug-In Hybrid Electric Vehicles Using Model Predictive Control With Route Preview

The paper proposes an adoption of slope,elevation,speed and route distance preview to achieve optimal energymanagement of plug-in hybrid electric vehicles(PHEVs).Theapproach is to identify route features from historical and real-time traffic data,in which information fusion model and trafficprediction model are used to improve the information accuracy.Then,dynamic programming combined with equivalent con-sumption minimization strategy is used to compute an optimalsolution for real-time energy management.The solution is thereference for PHEV energy management control along the route.To improve the system's ability of handling changing situation,the study further explores predictive control model in the real-time control of the energy.A simulation is performed to modelPHEV under above energy control strategy with route preview.The results show that the average fuel consumption of PHEValong the previewed route with model predictive control(MPC)strategy can be reduced compared with optimal strategy andbase control strategy.

OPTIMAL TORQUE CONTROL STRATEGY FOR PARALLEL HYBRID ELECTRIC VEHICLE WITH AUTOMATIC MECHANICAL TRANSMISSION

In parallel hybrid electrical vehicle （PHEV） equipped with automatic mechanical transmission （AMT）, the driving smoothness and the clutch abrasion are the primary considerations for powertrain control during gearshift and clutch operation. To improve these performance indexes of PHEV, a coordinated control system is proposed through the analyzing of HEV powertrain dynamic characteristics. Using the method of minimum principle, the input torque of transmission is optimized to improve the driving smoothness of vehicle. Using the methods of fuzzy logic and fuzzy-PID, the engaging speed of clutch and the throttle opening of engine are manipulated to ensure the smoothness of clutch engagement and reduce the abrasion of clutch friction plates. The motor provides the difference between the required input torque of transmission and the torque transmitted through clutch plates. Results of simulation and experiments show that the proposed control strategy performs better than the contrastive control system, the smoothness of driving and the abrasion of clutch can be improved simultaneously.