MPTC for PMSMs of EVs with Multi-Motor Driven System Considering Optimal Energy Allocation

© 1965-2012 IEEE. This paper presents a compound propulsion system with a high-speed permanent-magnet synchronous motor (PMSM) and two in-wheel motors for electric vehicles (EVs). In this paper, the longitudinal dynamic model of EVs is first presented. Then traction distribution ratio \alpha is introduced to express the traction distribution between the front and the rear axles. Moreover, the function of power consumption concerned with the traction distribution ratio \alpha is established. Therefore, the \alpha that minimizes the power consumption function is selected as the optimal traction distribution ratio. To improve the performance of motor controllers, the model predictive torque control (MPTC) method is employed for high-speed and in-wheel motor drives. Experimental comparison with field-oriented control (FOC) shows the advantages of MPTC in dynamic response. Finally, experimental comparisons and hardware-in-loop (HiL) tests are presented to verify the MPTC method and the proposed energy allocation method, respectively

In Depth Analysis of Power Balance, Handling, and the Traction Subsystem of an Articulated Skid-Steering Robot for Sustainable Agricultural Monitoring

This paper reports on the energy balance test performed on Agri.Q, an eight-wheel articulated robot intended to be a sustainable monitoring tool within the precision agriculture paradigm, and proposes an in-depth analysis of the traction subsystem in order to develop an appropriate traction allocation strategy to improve navigation through hilly or mountainous crops. Tests were conducted on the contribution of the orientable photovoltaic panel to the mission duration and overall sustainability, showing that a suitable mission plan, including dedicated charging phases, could significantly increase the robot’s operating time. A series of simulations of circular trajectories of different curvature and at different longitudinal velocities on flat ground were performed, with the aim of mapping the robot’s behaviour at steady state. The results of the simulations were analysed, paying particular attention to the required torques, manoeuvrability and forces exchanged on the ground. The simulations conducted demonstrated and extended previous results obtained on similar robotic architectures, which suffer from significant understeer behaviour due to significant lateral wheel slip during turning. They also showed the limitations of currently employed traction motors, but also the advantages of a proper traction allocation strategy involving the rear module. Article highlights. Agri.Q energy balance tests have been carried out to assess its endurance and sustainability The traction and handling behaviours of Agri.Q were mapped and discussed in detail in order to improve them Agri.Q has proven to be a basis for the future implementation of precision agriculture to advance the SDG

Path Planning and Energy Efficiency of Heterogeneous Mobile Robots Using Cuckoo–Beetle Swarm Search Algorithms with Applications in UGV Obstacle Avoidance

In this paper, a new meta-heuristic path planning algorithm, the cuckoo–beetle swarm search (CBSS) algorithm, is introduced to solve the path planning problems of heterogeneous mobile robots. Traditional meta-heuristic algorithms, e.g., genetic algorithms (GA), particle swarm search (PSO), beetle swarm optimization (BSO), and cuckoo search (CS), have problems such as the tenancy to become trapped in local minima because of premature convergence and a weakness in global search capability in path planning. Note that the CBSS algorithm imitates the biological habits of cuckoo and beetle herds and thus has good robustness and global optimization ability. In addition, computer simulations verify the accuracy, search speed, energy efficiency and stability of the CBSS algorithm. The results of the real-world experiment prove that the proposed CBSS algorithm is much better than its counterparts. Finally, the CBSS algorithm is applied to 2D path planning and 3D path planning in heterogeneous mobile robots. In contrast to its counterparts, the CBSS algorithm is guaranteed to find the shortest global optimal path in different sizes and types of maps

Optimal Direct Yaw Moment Control of a 4WD Electric Vehicle

This thesis is concerned with electronic stability of an all-wheel drive electric vehicle with independent motors mounted in each wheel. The additional controllability and speed permitted using independent motors can be exploited to improve the handling and stability of electric vehicles. In this thesis, these improvements arise from employing a direct yaw moment control (DYC) system that seeks to adapt the understeer gradient of the vehicle and achieve neutral steer by employing a supervisory controller and simultaneously tracking an ideal yaw rate and ideal sideslip angle. DYC enhances vehicle stability by generating a corrective yaw moment realized by a torque vectoring controller which generates an optimal torque distribution among the four wheels. The torque allocation at each instant is computed by finding a solution to an optimization problem using gradient descent, a well-known algorithm that seeks the minimum cost employing the gradient of the cost function. A cost function seeking to minimize excessive wheel slip is proposed as the basis of the optimization problem, while the constraints come from the physical limitations of the motors and friction limits between the tires and road. The DYC system requires information about the tire forces in real-time, so this study presents a framework for estimating the tire force in all three coordinate directions. The sideslip angle is also a crucial quantity that must be measured or estimated but is outside the scope of this study. A comparative analysis of three different formulations of sliding mode control used for computation of the corrective yaw moment and an evaluation of how successfully they achieve neutral steer is presented. IPG Automotive’s CarMaker software, a high-fidelity vehicle simulator, was used as the plant model. A custom electric powertrain model was developed to enable any CarMaker vehicle to be reconfigured for independent control of the motors. This custom powertrain, called TVC_OpenXWD uses the torque/speed map of a Protean Pd18 implemented with lookup tables for each of the four motors. The TVC_OpenXWD powertrain model and controller were designed in MATLAB and Simulink and exported as C code to run them as plug-ins in CarMaker. Simulations of some common maneuvers, including the J-turn, sinusoidal steer, skid pad, and mu-split, indicate that employing DYC can achieve neutral steer. Additionally, it simultaneously tracks the ideal yaw rate and sideslip angle, while maximizing the traction on each tire[CB1] . The control system performance is evaluated based on its ability to achieve neutral steer by means of tracking the reference yaw rate, stabilizing the vehicle by means of reducing the sideslip angle, and to reduce chattering. A comparative analysis of sliding mode control employing a conventional switching function (CSMC), modified switching function (MSMC), and PID control (HSMC) demonstrates that the MSMC outperforms the other two methods in addition to the open loop system

Actuators for Intelligent Electric Vehicles

This book details the advanced actuators for IEVs and the control algorithm design. In the actuator design, the configuration four-wheel independent drive/steering electric vehicles is reviewed. An in-wheel two-speed AMT with selectable one-way clutch is designed for IEV. Considering uncertainties, the optimization design for the planetary gear train of IEV is conducted. An electric power steering system is designed for IEV. In addition, advanced control algorithms are proposed in favour of active safety improvement. A supervision mechanism is applied to the segment drift control of autonomous driving. Double super-resolution network is used to design the intelligent driving algorithm. Torque distribution control technology and four-wheel steering technology are utilized for path tracking and adaptive cruise control. To advance the control accuracy, advanced estimation algorithms are studied in this book. The tyre-road peak friction coefficient under full slip rate range is identified based on the normalized tyre model. The pressure of the electro-hydraulic brake system is estimated based on signal fusion. Besides, a multi-semantic driver behaviour recognition model of autonomous vehicles is designed using confidence fusion mechanism. Moreover, a mono-vision based lateral localization system of low-cost autonomous vehicles is proposed with deep learning curb detection. To sum up, the discussed advanced actuators, control and estimation algorithms are beneficial to the active safety improvement of IEVs

Dynamics Modeling and Characteristics Analysis of Distributed Drive Electric Vehicles

Due to the short transmission chain, compact structure, and the feature of quick and accurate torque generation, distributed drive electric vehicle (DDEV) has attracted many researchers from academia and industry. The significantly redundant execution characteristic of four independently driven in-wheel motors also provides more potential to guarantee the vehicle dynamics performance. Moreover, the unique torque vector control of DDEV generates the direct yaw moment control mode. It has been proven to be effective to modify the vehicle steering characteristics. Through a reasonable torque vector allocation strategy, the energy-saving can also be realized. This chapter will introduce the distributed drive electric vehicle from the viewpoint of the dynamics modeling, stability performance analysis, and energy-saving strategy

Fault-tolerant control of electric vehicles with in-wheel motors using actuator-grouping sliding mode controllers

Although electric vehicles with in-wheel motors have been regarded as one of the promising vehicle architectures in recent years, the probability of in-wheel motor fault is still a crucial issue due to the system complexity and large number of control actuators. In this study, a modified sliding mode control (SMC) is applied to achieve fault-tolerant control of electric vehicles with four-wheel-independent-steering (4WIS) and four-wheel-independent-driving (4WID). Unlike in traditional SMC, in this approach the steering geometry is re-arranged according to the location of faulty wheels in the modified SMC. Three SMC control laws for longitudinal velocity control, lateral velocity control and yaw rate control are designed based on specific vehicle motion scenarios. In addition the actuator-grouping SMC method is proposed so that driving actuators are grouped and each group of actuators can be used to achieve the specific control target, which avoids the strong coupling effect between each control target. Simulation results prove that the proposed modified SMC can achieve good vehicle dynamics control performance in normal driving and large steering angle turning scenarios. In addition, the proposed actuator-grouping SMC can solve the coupling effect of different control targets and the control performance is improved

Metro Trains Equipped Onboard withSupercapacitors: a Control Technique forEnergy Saving

The paper deals with the use of onboard supercapacitors for metro trains. The practical utilization of supercapacitors requires suitable power converters for the regulation of power flows between the catenary and the electrical drives of the power-train. These converters operate in dc current and have to be bi-directional in order to allow the charge and discharge of supercapacitors. The mathematical model of the whole electrical drive has been developed and the main features of the control strategy have been presented. The control is capable of limiting the peak currents of the contact line and recovering partially the kinetic energy of the train during the braking periods. Simulations prove that the suggested control strategy is very effective for both purposes. Experimental tests made on a scaled prototype, representing the translating masses of a train, fully confirm the results of the simulations