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New challenges arise for engineers with the emergence of Hybrid Electrical Vehicles (HEV) and Battery Electrical Vehicles (BEV). As an electric motor has a lower overall noise emission compared to an Internal Combustion Engine (ICE), the overall noise level inside an EM driven car’s cabin is more colored by road noise and windnoise. That being said, the EM can still be very audible because of its prominent high-pitched tonal content, linked to the machine design (number of slots, poles). Hence, in view of driver and passenger comfort, reduction of cabin noise also involves optimizing the noise mission of electric motors. The noise produced by an electrical machine in operation can be assessed early on in the design process using simulation methods. This paper presents currently available approaches for assessing during the ideation phase the noise induced by a brushless Permanent Magnet Synchronous Machine (PMSM) which are widely used in electrical vehicles.

Improving fuel efficiency often affects NVH performance. Modifying a vehicle’s design in the latter stages of development to improve NVH performance is often costly. Therefore, to optimize the cost performance, a Multi-Attribute Balancing (MAB) approach should be employed in the early design phases. This paper proposes a solution based on a unified 1D system simulation model across different vehicle performance areas. In the scope of this paper the following attributes are studied: Fuel economy, Booming, Idle, Engine start and Drivability. The challenges to be solved by 1D simulation are the vehicle performance predictions, taking into account the computation time and accuracy. Early phase studies require a large number of scenarios to evaluate multiple possible parameter combinations employing a multi-attribute approach with a systematic tool to ease setup and evaluation according to the determined performance metrics.