This paper was produced for the 2019 NAFEMS World Congress in Quebec Canada
The automotive industry is experiencing disruptive changes with electric, autonomous & connected mobility. Automakers (OEMs) and suppliers are entering a new phase in powertrain systems – ramping down internal combustion engine design and production and ramping up design and production of electric vehicles. Electric drive systems, comprised of the electric machine and a gearbox, are complex and their performance in different domains needs to be evaluated to improve and optimize their design.
One of the challenges in electric drive engineering is to ensure acoustic passenger comfort. Electric machines and gearboxes can produce tonal noises that are perceived as unpleasant. The internal combustion engine in traditional vehicles helped to mask some of these noises. Now with the general reduced noise level in electric vehicles, in particular at low and medium speeds, there needs to be a special focus on the noise and vibration behavior of these components.
To analyze the noise and vibration behavior of electric drive systems, multi-domain analysis with linked simulations of the entire system are generally necessary. The basis for the noise and vibration analysis is an elastic structural model of the electric drive system. A finite element model of the stator in an interior permanent magnet synchronous machine (IPMSM) as well as the overall gearbox housing is used to characterize the dynamics of the structure. A reduced-order model is obtained using the dynamic substructuring technique. This model representation is important to describe the dynamic behavior of the structure with relatively few degrees of freedom thereby achieving much faster computations with negligible loss in accuracy for the desired use in the noise and vibration analysis.
Dynamic electromagnetic (EMAG) forces acting on the stator and rotor of the electric machine lead to structural vibrations. Therefore, electromagnetic simulation needs to be carried out to determine forces and torques for the desired speed range of the machine. Multibody simulation is the ideal tool to study noise and vibration phenomena of complex drive systems because of the higher abstraction level used for the models. In contrast to full-scale finite element models with generic 3D contact formulations, SIMULIA Simpack Multibody Simulation offers a large catalogue of application- specific elements. Those elements are mostly based on analytical formulas with the aim of modeling a part of the system with exactly the required level of detail for reducing unnecessary complexity and simulation effort while sustaining the highest level of accuracy for the desired application. Apart from the electromagnetic forces from the preceding electromagnetic simulation, dynamic gear forces due to varying contact stiffness are the other main excitation source in the electric drive. Furthermore, it is important to model the shafts as flexible, which can be done by either using a beam model or using dynamic substructures like that of the housing. The rolling bearings, which support the shafts relative to the housing, are also modeled using effective analytical methods.
Multibody simulation brings together the mechanical properties of the flexible components with the typical non-linear excitation mechanisms, allowing for the efficient study of noise and vibration phenomena in electric drive systems. A subsequent vibro-acoustics analysis can then take the surface vibrations of the housing and obtain the air-born noise around that structure.
Further, for engineers to easily run design trade-off studies, parametric optimizations and ultimately arrive at an optimal design configuration, the holistic use of parametric models is essential. Using our coupled multiphysics simulation framework, we will demonstrate how the multi-domain analysis of an electric drivetrain is carried out by integrating structural, electromagnetic and multibody system simulations. Additionally, the framework places emphasis on automated model updates and process execution, which dramatically reduces the time and effort to study numerous design alternatives.