Why Simulation Is Essential for EV Machine Design
In Electric Vehicles (EVs) a traction motor delivers torque to the drive wheels. This means that the vehicle performance is totally determined by the torque-speed or power speed characteristic of the traction motor. This means that an EV motor drive must be capable of offering a high torque at low speed for starting and acceleration, and a high power at high speed for cruising.
Engineers who design EVs need simulation services and tools that can quickly, yet very accurately, be employed to ensure that the essential criteria are met. According to one source, the method of choice by engineers who design EVs is the ﬁnite element method (FEM).
What is FEM?
The finite element method (FEM) is a numerical technique for finding approximate solutions to boundary value problems for partial differential equations. It is also referred to as finite element analysis (FEA). FEM subdivides a large problem into smaller, simpler, parts, called finite elements. Historically, FEM has been used as a ﬁnal check, the last step, of the design process before releasing the design to manufacturing. But, many firms have found that it is beneficial to move simulation to a much earlier place in the design cycle. One of the biggest reasons for this change is because virtual design technology has improved to the point that early simulations can be made without compromising accuracy.
By using high-performance computing (HPC) and advanced FEM, design engineers attain higher machine eﬃciencies with less material, lower costs and greater competitive edge.
From FEM to FEA
FEM is best understood from its practical application, known as finite element analysis (FEA). FEA, as applied in engineering, is a computational tool for performing engineering analysis. It includes the use of mesh generation techniques for dividing a complex problem into small elements, as well as the use of software programs coded with FEM algorithm.
In applying FEA, the complex problem is usually a physical system, such as an EV machine, with the underlying physics expressed in either PDE or integral equations, while the divided small elements of the complex problem represent different areas in the physical system. FEA is a good choice for analyzing problems overcomplicated systems (like cars and oil pipelines).
The entire solution domain in which an electrical machine, like an EV, operates is most commonly characterized by an eﬃciency map. To predict the eﬃciency map through simulation, a relatively large number of data points need to be calculated. The extraction and mapping of these data points show that the utilization of EVs enables a step change in vehicle efficiency when compared to vehicles powered by internal combustion engines. Such mapping can study the whole vehicle efficiency and energy consumption over a range of vehicle speeds and battery load points.
This type of simulation determines how a particular design will perform, and enables a design engineer to know how to improve the design, for instance, by using less material, or making it easier to manufacture. Using simulation early in the design phase, the engineering team can perform any type of optimization desired.
EV Design is a Multiphysics Problem
Once the design engineer is able to determine the optimum topology, it is critical to determine the eﬀects of losses and distributed forces on the thermal as well as noise and vibration of the EV. For example, electrical energy is applied to the machine via power electronic devices, such as inverters, which introduce temporal harmonics to the system. This electrical energy is converted to magnetic energy, which in turn makes the rotor rotate, introducing spatial harmonics. This conversion is not 100 percent eﬃcient, and the losses that are incurred are realized as an increase in temperature in the electrical machine that needs to be reduced. Finally, the magnetic forces that cause the rotor to rotate are the source of stresses and strains across the machine that introduce noise and vibration. All of these physical properties, electrical-magnetic-thermal-stress-acoustic, need to be addressed by the design team.