Yee-Pien Yang

This paper applies a dynamic path planning and model predictive control (MPC) to simulate self-driving and parking for an electric van on a hardware-in-the-loop (HiL) platform. The hardware platform is a simulator which consists of an electric power steering system, accelerator and brake pedals, and an Nvidia drive PX2 with a robot operating system (ROS). The vehicle dynamics model, sensors, controller, and test field map are virtually built with the PreScan simulation platform. Both manual and autonomous driving modes can be simulated, and a graphic user interface allows a test driver to select a target parking space on a display screen. Three scenarios are demonstrated: forward parking, reverse parking, and obstacle avoidance. When the vehicle perceives an obstacle, the map is updated and the route is adaptively planned. The effectiveness of the proposed MPC is verified in experiments and proved to be superior to a traditional proportional–integral–derivative controller with regards to safety, energy-saving, comfort, and agility.

A torque and battery distribution (TBD) strategy is proposed for saving energy for an electric vehicle (EV) that is driven by three traction motors. Each traction motor is driven by an independent inverter and a battery pack. When the vehicle is accelerating or cruising, its vehicle control unit determines the optimal torque distribution of the three motors by particle swarm optimization (PSO) theory to minimize energy consumption on the basis of their torque–speed–efficiency maps. Simultaneously, the states of charge (SOC) of the three battery packs are controlled in balance for improving the driving range and for avoiding unexpected battery depletion. The proposed TBD strategy can increase 7.7% driving range in the circular New European Driving Cycle (NEDC) of radius 100 m and 28% in the straight-line NEDC. All the battery energy can be effectively distributed and utilized for extending the driving range with an improved energy consumption efficiency.

This paper proposes a design of a surface-mounted permanent magnet (SPM) motor with a magnet surface of a sinusoidal pulsewidth-modulation (SPWM) shape. The fundamental harmonic of the flux density distribution over the SPWM-shaped magnet surface is sinusoidal, which makes the back electromotive force induced in the phase winding close to sinusoidal. Slots can be cut easily into the magnet to form an SPWM-shaped surface, and less rare-earth magnet material is used if the SPWM-shaped permanent magnet (PM) is sintered or bonded in the molds. The optimal SPWM magnet shape on the SPM motor for an electric scooter is designed by maximizing the output torque and efficiency and minimizing the magnet volume and is verified by the finite-element analysis. Prototype motors are fabricated with magnets of various shapes, with or without an SPWM surface. The amount of rare-earth magnet material used in the motor with the SPWM-shaped PMs is 9.4%-13.2% less than that without the SPWM-shaped PMs, while the maximum torque is reduced by only 3%-5.4%.

This paper proposes a multi-phasic coupling analysis and test of a 50 kW traction motor for electric vehicles. The temperature-dependent properties of the electrical and magnetic materials of the interior permanent magnet traction motor are not negligible over a wide operation range of the vehicle. The heat produced by the electromagnetic power loss changes the motor’s properties, and in turn the motor performance changes to produce a different power loss. This two-way coupled electromagnetic and thermal-fluid analysis of the torque and speed curve and the transient thermal response at a rated operation point are simulated and compared with the traditional one-way coupling analysis. The simulation results are also compared with and proved by experiments on a prototype motor. The experimental results show that it is critical and necessary to predict the motor performance by means of the proposed two-way coupling analysis that provides more accurate information than the traditional one-way coupling analysis.

This study proposes a real‐time torque‐distribution strategy for a pure electric vehicle (EV) with multi‐electric propulsion system. This electric propulsion system is composed of three motors – an indirectly driven traction motor for front wheels and two in‐wheel motors installed inside both rear wheels. Their torque distribution is determined by particle swarm optimisation (PSO) theory for minimising energy consumption according to the torque‐speed‐efficiency maps of all the traction motors. The energy consumption over the New European Driving Cycle is analysed for the EV with multiple traction motors. Simulation results by hardware‐in‐the‐loop show that the driving efficiency of the proposed real‐time torque‐distribution strategy by the PSO is close to the results from the global optimisation method by dynamic programming.

This paper proposes a driving-scenario oriented optimal design of an axial-flux permanent-magnet (AFPM) motor for an electric vehicle. The target torque and speed (TN) curve is defined as three operation zones-constant torque, maximum direct current, and maximum voltage—based on the driving scenario. The AFPM motor is designed to minimize energy consumption based on the motor weight and the frequent operating points of a driving cycle. The final result shows that the electric vehicle driven by the proposed AFPM motor consumes about 15% less energy than motors designed using traditional methods.

This paper proposes an optimal design of a middle motor integrated into a mid-drive unit for pedal electric cycles. This middle motor is an axial-flux permanent magnet brushless DC motor with a stator plate. Facing this plate is a rotor plate that acts as an eccentric component of a cycloidal reducer next to the stator. Both the middle motor and cycloidal reducer are easily installed on the same axle of the bike crankset. In the preliminary design, driving requirements are used to make the middle motor specifications. The numbers of stator slots and magnet poles on the rotor were chosen to achieve the best winding factor, and the winding layout was determined accordingly. A one-dimensional magnetic circuit model of the middle motor was built, and its shape was optimized utilizing a multifunctional optimization system tool. Finally, the resulting design was verified and refined by a finite element analysis. A prototype of the middle motor was fabricated with a stator made of a soft magnetic composite and integrated with a cycloidal reducer. Experimental results show that the motor has a sinusoidal back electromotive force. Additionally, it is easily controlled by sinusoidal currents with acceptable torque and speed curves.

This paper proposes a driving‐scenario oriented design of an axial‐flux permanent‐magnet synchronous motor for a pedal electric cycle (Pedelec). Traditional motors are usually designed according to a torque and speed (TN) curve with two operation zones – constant torque and constant power, without being closely related to a driving scenario. The proposed design method defines the TN curve with three operation zones – constant torque, maximum DC current and maximum voltage, which are specified by a driving scenario, the modulation method of motor drive and basic torque and voltage equations of motors. This target TN curve provides admissible ranges for the back electromotive force constant and phase resistance of the motor to be designed. A systematic design procedure is introduced by a quasi‐three‐dimensional (3D) magnetic circuit model, a multi‐objective optimisation process for sizing the motor and a finite element analysis for verifying and refining the design. The resulting TN curve of the proposed Pedelec motor is proved to be very close to the target TN curve that is prescribed by the driving scenario, and motor and drive parameters.

This paper proposes the novel design of a surface-mounted permanent-magnet (SPM) motor with a magnet surface that is a sinusoidal pulse-width-modulation (SPWM) shape for an electric scooter. The optimal SPWM magnet shape on the SPM motor was designed by maximizing the output torque and efficiency and minimizing the magnet volume, and was verified with finite element analysis. The prototype motors were fabricated with magnets of various shapes, with or without an SPWM surface. The experimental results showed that the prototype motors with SPWM-shaped PMs had a high percentage of fundamental harmonics. The amount of rare-earth magnet material used in the motor with SPWM-shaped PMs was less than the amount used in motors without SPWM-shaped PMs.

This paper proposes a vehicle stability control (VSC) during the electric propulsion failure of an electric vehicle (EV). This EV is driven by three traction motors; one traction motor is responsible for two front wheels, while two wheel motors are responsible for rear wheels. When any one of the traction motors fails, the proposed VSC calculates new torque distribution according to a direct yaw-moment controller and a slip ratio controller. This VSC strategy is implemented in a digital signal processor. A real-time hardware-in-the-loop test is then performed on a dynamometer with a motor acting as one of the rear wheel motors, while the EV and other two traction motors are modeled with commercially available simulation tools. Experimental results show that the proposed VSC strategy is able to keep the EV safe and stable after its electric propulsion failure is detected.