Abstract With emission norms getting more and more stringent, the trend is shifting towards electric and hybrid vehicles. Electric motor replaces engine as the prime mover in these vehicles. Though these vehicles are quieter compared to their engine counterpart, they exhibit certain annoying sound quality perception. There is no standard methodology to predict the noise levels of these motors. Electric motor noise comprises of mainly three sources viz., Aerodynamic, Electromagnetic and Mechanical. A methodology has been developed to predict two major noise sources of electric motor out of the three above viz. Mechanical and Aerodynamic noise. These two noise sources are responsible for the tonal noise in an electric motor. Aerodynamic noise arises most often around the fan, or in the vicinity of the machine that behaves like a fan. This noise is predominant at higher motor speed and also in electric vehicle due to higher speed fluctuation. Prediction of the aerodynamic noise primarily has been done using Computational Fluid Dynamic tool. Ffowcs Williams-Hawkings (FW-H) model is used to predict the aerodynamic noise. The Mechanical noise is predominant at the intermediate speed of the motor. The vibrations caused by this noise source results in unsatisfactory driving experience for the end user. Free-free modal analysis is performed for calculating the mode shapes and modal frequencies of the motor. Further frequency response analysis is carried out to calculate the surface vibration velocity of the motor. Sound power evaluation of the motor has been carried out using a Boundary Element Method (BEM) tool. The aerodynamic noise was validated with experimental measurement and it was found to be in good agreement. This methodology has helped in evaluating the motor performance at prototype stage itself hence reducing product development cycle time. Introduction With increasing dependency on fossil fuels for mobility and alarming rates of depletion of the reservoirs the trend is shifting towards more efficient and high performance electric and hybrid vehicles. Also in motor drive control system, the important subject is not only the improvement of electric energy efficiency but also suppressing drive train vibration and acoustic noise by requirement of high drivability. Though electric vehicles are much quieter than their engine counterpart, there are still lots of improvement needed for getting better acoustic quality from electric vehicles. In IC engines the engine masks the unwanted noise but in case of electric vehicle there is no masking effect. Also there are various techniques developed to predict and identify the noise sources from IC engines but there are not many specific techniques available to determine the noise sources of an electric motor. With lightweight design stretched to its limits to maximize driving range and performance while moderating the battery cost, achieving acceptable NVH performance becomes greater challenge. The interior noise of the electric vehicles is marked by high frequency tonal noise components which can subjectively perceived as annoying. Disturbing noises shared by the other devices like Heating, ventilation and air conditioning (HV AC), battery fan, alternator, transmission system, oil pump, etc. are no longer masked by the combustion engine noise and give rise to complex sound signatures. New sound perception challenges emerge due to the increased high frequencies and tonality nature of the vehicle sounds and new modulation characteristics. New noise transfer control challenges are generated on one hand due to higher frequency ranges of electric vehicles sources and on other hand by sensitive weight constraints. The different nature of the NVH problems not only requires novel technical solutions but also impacts the way the NVH analysis and engineering process is to be performed. As a consequence, the automotive R&D departments are currently reviewing and innovating their NVH processes an