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.

Design and Optimization of Interior Permanent Magnet(IPM)Motor for Electric Vehicle Applications

This paper explores some design parameters of an interior permanent magnet synchronous motor that contribute to enhancing motor performance.Various geometry parameters such as magnet dimension,machine diameter,stator teeth height,and number of poles are analyzed to compare overall torque,power,and torque ripples in order to select the best design parameters and their ranges.Pyleecan,an open-source software,is used to design and optimize the motor for electric vehicle applications.Following optimization with Non-dominated Sorting Genetic Algorithm(NSGA-Ⅱ),two designs A and B were obtained for two objective functions and the corresponding torque ripples values of the design A and B were later reduced by 32%and 77%.Additionally,the impact of different magnet grades on the output performances is analyzed.

MPC-based Torque Distribution for Planar Motion of Four-wheel Independently Driven Electric Vehicles:Considering Motor Models and Iron Losses

The most critical obstacle for four-wheel independently driven electric vehicles(4WID-EVs)is the driving range.Being the actuators of 4WID-EVs,motors account for its major power consumption.In this sense,by properly distributing torques to minimize the power consumption,the driving range of 4WID-EV can be effectively improved.This paper proposes a model predictive control(MPC)-based torque distribution scheme,which minimizes the power consumption of 4WID-EVs while guaranteeing its tracking performance of planar motions.By incorporating the motor model considering iron losses,the optimal torque distribution can be achieved without an additional torque controller.Also,for this reason,the proposed control scheme is computationally efficient,since the power consumption term to be optimized,which is expressed as the product of the motor voltages and currents,is much simpler than that derived from the efficiency map.With reasonable simplification and linearization,the MPC problem is converted to a quadratic programming problem,which can be solved efficiently.The simulation results in MATLAB and CarSim co-simulation environments demonstrate that the proposed scheme effectively reduces power consumption with guaranteed tracking performance.

A novel functional electrical stimulation-control system for restoring motor function of post-stroke hemiplegic patients

Hemiparesis is one of the most common consequences of stroke. Advanced rehabilitation techniques are essential for restoring motor function in hemiplegic patients. Functional electrical stimulation applied to the affected limb based on myoelectric signal from the unaffected limb is a promising therapy for hemiplegia. In this study, we developed a prototype system for evaluating this novel functional electrical stimulation-control strategy. Based on surface electromyography and a vector machine model, a self-administered, muki-movement, force-modulation functional electrical stimulation-prototype system for hemiplegia was implemented. This paper discusses the hardware design, the algorithm of the system, and key points of the self-oscillation-prone system. The experimental results demonstrate the feasibility of the prototype system for further clinical trials, which is being conducted to evaluate the efficacy of the proposed rehabilitation technique.

Rebuilding motor function of the spinal cord based on functional electrical stimulation

Rebuilding the damaged motor function caused by spinal cord injury is one of the most serious challenges in clinical neuroscience.The function of the neural pathway under the damaged sites can be rebuilt using functional electrical stimulation technology.In this study,the locations of motor function sites in the lumbosacral spinal cord were determined with functional electrical stimulation technology.A three-dimensional map of the lumbosacral spinal cord comprising the relationship between the motor function sites and the corresponding muscle was drawn.Based on the individual experimental parameters and normalized coordinates of the motor function sites,the motor function sites that control a certain muscle were calculated.Phasing pulse sequences were delivered to the determined motor function sites in the spinal cord and hip extension,hip flexion,ankle plantarflexion,and ankle dorsiflexion movements were successfully achieved.The results show that the map of the spinal cord motor function sites was valid.This map can provide guidance for the selection of electrical stimulation sites during the rebuilding of motor function after spinal cord injury.

Electromyographic evaluation of functional electrical stimulation to injured oculomotor nerve

Functional electrical stimulation delivered early after injury to the proximal nerve stump has been proposed as a therapeutic approach for enhancing the speed and specificity of axonal regeneration following nerve injury. In this study, the injured oculomotor nerve was stimulated functionally by an implantable electrode. Electromyographic monitoring of the motor unit potential of the inferior oblique muscle was conducted for 12 weeks in two injury groups, one with and one without electric stimulation. The results revealed that, at 2, 4, 6, 8 weeks after functional electric stimulation of the injured oculomotor nerve, motor unit potentials significantly increased, such that amplitude was longer and spike duration gradually shortened. These findings indicate that the injured oculomotor nerve has the potential for regeneration and repair, but this ability is not sufficient for full functional recovery to occur. Importantly, the current results indicated that recovery and regeneration of the injured oculomotor nerve can be promoted with functional electrical stimulation.

STUDY ON POWER SPARE COEFFICIENT OF ELECTRICAL MOTOR IN LARGE PUMP STATION BASED ON RELIABILITY

Characters of head of low head pump station and the pump shaft power areanalyzed. Influence of each single factor on pump shaft power is expressed as change of specificshaft power. (non-dimensional) and the probability density function is determined. Influences ofmultiple factors on pump shaft power are analyzed. Method of calculating none over-loadedprobability of motor by integration by successive reductions is put forward and then relationbetween power spare coefficient and none over-loaded reliability of electric motor is established.Influences of all factors on pump shaft power being considered completely; power spare coefficientsof motor are calculated in three kinds of heads (changing and unchanging), two kinds of dirty-outconditions. Electrical motor power spare coefficients should be chosen as 1.20 approx 1.44, 1.11approx 1.19, 1.09 approx.14 respectively when pump heads are 4, 7, 9.5 m. The results mean much toreasonable choose of electrical motors in large pump stations, increasing reliability of pump unitsand saving equipment investment.

Review of Three-phase Soft Switching Inverters and Challenges for Motor Drives

For electric vehicles (EVs),it is necessary to improve endurance mileage by improving the efficiency.There exists a trend towards increasing the system voltage and switching frequency,contributing to improve charging speed and power density.However,this trend poses significant challenges for high-voltage and high-frequency motor controllers,which are plagued by increased switching losses and pronounced switching oscillations as consequences of hard switching.The deployment of soft switching technology presents a viable solution to mitigate these issues.This paper reviews the applications of soft switching technologies for three-phase inverters and classifies them based on distinct characteristics.For each type of inverter,the advantages and disadvantages are evaluated.Then,the paper introduces the research progress and control methods of soft switching inverters (SSIs).Moreover,it presents a comparative analysis among the conventional hard switching inverters (HSIs),an active clamping resonant DC link inverter (ACRDCLI) and an auxiliary resonant commuted pole inverter (ARCPI).Finally,the problems and prospects of soft switching technology applied to motor controllers for EVs are put forward.

Efficiency of Model Induction Motor Using Various Non-Oriented Electrical Steels

The performance of a 3-phase 6-pole 400 W inverter-drive induction motor was investigated using a variety of non-oriented electrical steels for stator core at PWM inverter fundamental wave frequencies of 30 to 300 Hz. There existed an optimum Si content of the material depending on the tooth flux density. Both reduction of material thickness and stress-relief annealing of the stator core improved the motor efficiency. The influence of Si content on the efficiency was small at lower PWM frequencies, while at higher frequencies the motor efficiency increased with increasing Si content. The Cu loss WC increased and the Fe loss Wi counteractiveiy decreasedwith increasing Si content at lower frequencies; while at higher frequencies Wi had dominant effect on the efficiency. Newly developed materials RMA, having lower Fe losses after stress-relief annealing and higher flux densities with lower Si contents, showed motor efficiencies superior to conventional J1S grade materials with comparable Fe losses.

Environmental Assessment and Dielectric Performances of the Secondary Electrical Insulation in Low Voltage Motors Impregnated by Different Techniques

A recent technique, using to potentially replace the conventional impregnating one in low voltage electric motors, has been studied in this communication. The conventional technique that uses?both primary and secondary insulations;?i.e.: enamel and varnish, has been compared to this recent technique which only uses one component,?i.e.: self-bonding wires. Self-bonding wires polymerization is very quick compared to that of the conventional technique. Environmental impact and both dielectric and mechanical properties of these two techniques have been estimated and compared. The goal is to estimate if this recent technique has not only a better environmental footprint but also good technical properties. The dielectric properties that have been measured are the dielectric strength and?the lifetime under pulse?voltage while mechanical consists in measuring the bonding strength that is crucial for impregnation.?For that purpose, a Life Cycle Assessment (LCA) that can simultaneously evaluatenumerous impacts on ground, water and air,?has been performed. The results show clearly that the recent technique significantly reduces the environmental footprint. Both mechanical and dielectric properties are then compared and analyzed.

Health Monitoring of Induction Motor Using Electrical Signature Analysis

Induction motors have been widely used across industry,particularly with smaller loads and fixed speed services.Existing works focus on fault detection of induction motors without considering the shutdown time and production in industry.Therefore,this work aims to monitor the health conditions of the induction motor continuously through electrical signature analysis(ESA).The proposed technique is capable of predicting different kinds of faults,i.e.,rotor faults,stator phase imbalances,and supply cable faults at early stages.Moreover,ESA in real time is implemented.Thereafter,these current spectra were analyzed in frequency domain and compared with healthy current spectra.Performance evaluation is implemented by observing these spectra under different faulty conditions.A comparative study is made and analyzed through MATLAB simulations.

Output torque and temperature control technologies for an electrical screw press motor

The DSC(direct self control) of speed regulation technology was applied to drive a motor running at a certain overloading ratio in intermittent working conditions.To control motor temperatures rising effectively,a finite element method with an iterative approach was applied to simulate real working conditions and analyze the temperature rising of the inner part of the motor.Application of DSC speed regulation realizes the invariable torque output quickly and avoids the peak current at the start state in favor of the motor temperature decreasing.Based on an analysis with the finite limit method,some effective measures were taken to improve the ability of the motor to expel heat.The overload ability of the motor was improved and the stable motor temperature rising was obtained,fulfilling the demands of electrical screw presses.

Unsupervised Electric Motor Fault Detection by Using Deep Autoencoders

Fault diagnosis of electric motors is a fundamental task for production line testing, and it is usually performed by experienced human operators. In the recent years, several methods have been proposed in the literature for detecting faults automatically. Deep neural networks have been successfully employed for this task, but, up to the authors' knowledge, they have never been used in an unsupervised scenario. This paper proposes an unsupervised method for diagnosing faults of electric motors by using a novelty detection approach based on deep autoencoders. In the proposed method, vibration signals are acquired by using accelerometers and processed to extract LogMel coefficients as features. Autoencoders are trained by using normal data only, i.e., data that do not contain faults. Three different autoencoders architectures have been evaluated: the multilayer perceptron(MLP) autoencoder, the convolutional neural network autoencoder, and the recurrent autoencoder composed of long short-term memory(LSTM) units. The experiments have been conducted by using a dataset created by the authors, and the proposed approaches have been compared to the one-class support vector machine(OC-SVM) algorithm. The performance has been evaluated in terms area under curve(AUC) of the receiver operating characteristic curve, and the results showed that all the autoencoder-based approaches outperform the OCSVM algorithm. Moreover, the MLP autoencoder is the most performing architecture, achieving an AUC equal to 99.11 %.

Early electrical field stimulation prevents the loss of spinal cord anterior horn motoneurons and muscle atrophy following spinal cord injury

Our previous study revealed that early application of electrical field stimulation（EFS） with the anode at the lesion and the cathode distal to the lesion reduced injury potential, inhibited secondary injury and was neuroprotective in the dorsal corticospinal tract after spinal cord injury（SCI）. The objective of this study was to further evaluate the effect of EFS on protection of anterior horn motoneurons and their target musculature after SCI and its mechanism. Rats were randomized into three equal groups. The EFS group received EFS for 30 minutes immediately after injury at T_（10）. SCI group rats were only subjected to SCI and sham group rats were only subjected to laminectomy. Luxol fast blue staining demonstrated that spinal cord tissue in the injury center was better protected; cross-sectional area and perimeter of injured tissue were significantly smaller in the EFS group than in the SCI group. Immunofluorescence and transmission electron microscopy showed that the number of spinal cord anterior horn motoneurons was greater and the number of abnormal neurons reduced in the EFS group compared with the SCI group. Wet weight and cross-sectional area of vastus lateralis muscles were smaller in the SCI group to in the sham group. However, EFS improved muscle atrophy and behavioral examination showed that EFS significantly increased the angle in the inclined plane test and Tarlov＇s motor grading score. The above results confirm that early EFS can effectively impede spinal cord anterior horn motoneuron loss, promote motor function recovery and reduce muscle atrophy in rats after SCI.

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.

Torque Distribution of Electric Vehicle with Four In-Wheel Motors Based on Road Adhesion Margin

With the worsening of energy crisis and environmental pollution,electric vehicles with four in?wheel motors have been paid more and more attention. The main research subject is how to reasonably distribute the driving torque of each wheel. Considering the longitudinal motion,lateral motion,yaw movement and rotation of the four wheels,the tire model and the seven DOF dynamic model of the vehicle are established in this paper. Then,the torque distribution method is proposed based on road adhesion margin,which can be divided into anti ? slip control layer and torque distribution layer. The anti?slip control layer is built based on sliding mode variable structure control,whose main function is to avoid the excessive slip of wheels caused by road conditions. The torque distribution layer is responsible for selecting the torque distribution method based on road adhesion margin. The simulation results show that the proposed torque distribution method can ensure the vehicle quickly adapt to current road adhesion conditions,and improve the handling stability and dynamic performance of the vehicle in the driving process.

Sensorless torque control scheme of induction motor for hybrid electric vehicle

In this paper, the sensorless torque robust tracking problem of the induction motor for hybrid electric vehicle （HEV） applications is addressed, Because motor parameter variations in HEV applications are larger than in industrial drive system, the conventional field-oriented control （FOC） provides poor performance. Therefore, a new robust PI-based extension of the FOC controller and a speed-flux observer based on sliding mode and Lyapunov theory are developed in order to improve the overall performance. Simulation results show that the proposed sensorless torque control scheme is robust with respect to motor parameter variations and loading disturbances. In addition, the operating flux of the motor is chosen optimally to minimize the consumption of electric energy, which results in a significant reduction in energy losses shown by simulations.

Design andtwo-objective simultaneous optimization of torque controller for switched reluctance motor in electric vehicle

In order to reduce the torque ripple,increase the average torque and optimize the drive performance of the switched reluctance motor (SRM),the nonlinear dynamic model of SRM is established in the MATLAB /Simulink environment.The effects of the turn-on and turn-off angles are investigated by the simulation results of the dynamic model,and the function is made among the rotor speed,turn-on angle and turn-off angle.To optimize the torque dynamic performance,the two-objective simultaneous optimization function is proposed by two weight factors.And the optimized turn-on and turn-off angles as functions of rotor speed are developed by using the simultaneous optimization method.Then the optimized torque controller is designed based on the optimized turn-on and turn-off angles.The simulation results show that the optimized torque controller designed in this paper can effectively reduce the torque ripple and increase the average torque,and optimize the torque dynamic performance of the SRM.

Driving Range Parametric Analysis of Electric Vehicles Driven by Interior Permanent Magnet Motors Considering Driving Cycles

This paper presents parametric analysis of driving range of electric vehicles driven by V-type interior permanent magnet motors aiming at maximum driving range,i.e.,minimal total energy consumption of the motors over a driving cycle.Influence of design parameters including tooth width,slot depth,split ratio(the ratio of inner diameter to outer diameter of the stator),and V-type magnet angle on the energy consumption of the motors and driving range of electric vehicles over a driving cycle is investigated in detail.The investigation is carried out for two typical driving cycles with different characteristics to represent different conditions:One is high-speed,low-torque cycle-Highway Fuel Economy Test and the other is low-speed,high-torque cycle-Artemis Urban Driving Cycle.It shows that for both driving cycles,the same parameters may have different influence on the energy consumption of the motors,as well as driving range of electric vehicles.

Auto-Test on Motor Temperature Rising in Electric Vehicles with Mutual MRAS

A new method to calculate the motor temperature rising in electric vehicle （EV） is proposed based on the stator resistance identification. The measure theory of the motor temperature rising with the stator resistance is discussed at first. An enhanced magnetism motor dynamic math model is built which is the research object. Then the resistance identification system model is built on the mutual model reference adaptive,system （MRAS） theory. The simulation diagram of the mutual MRAS model is constructed and the resistance identification performance is studied in different motor states. Simulation results indicate that the stator resistance identification model with the mutual MRAS is effective. At the same time, the identification of motor temperature rising is possible with the identification of the stator resistance.