# Interior Sound Quality Prediction of Pure Electric Vehicles Based on Transfer Path Synthesis
## 1 Introduction  
The growing energy crisis has severely challenged the future development of conventional internal combustion engine vehicles (ICEVs). Environmentally friendly, low-carbon, and low-emission pure electric vehicles (PEVs) are the certain future trend in the development of the automotive industry. The low noise is a remarkable feature of PEVs [1, 2]. However, as the motor, electronic control components, and inverter units produce a large amount of annoying high-frequency noise, the noise waveform and spectral structure inside the vehicle are very different from those inside ICEVs, and the subjective evaluations of drivers and passengers significantly differ between the two types of vehicles [3, 4]. Although PEVs are quieter than ICEVs, the subjective perceptions of the driver are unsatisfactory, and many interior sound quality (SQ) problems negatively affect the acoustics of PEV and reduce the comfort of the vehicle ride [5, 6, 7, 8]. Transfer path analysis (TPA) and transfer path synthesis (TPS) techniques have been widely used in the automotive noise, vibration, and harshness (NVH) industry [9, 10, 11, 12, 13, 14]. TPA technology has been a mainstay of ICEVs and has been more recently considered for EVs. In-vehicle noise measurements, TPA and TPS accurately determine the composition of specific-frequency noises and their associated transfer paths. Besides assisting SQ design, TPA and TPS provide everyday simplified measurements for commercial applications. The hybrid TPA method developed in [9, 10] predicts the interior noise caused by the structure-borne path of a powertrain. This technique is useful for design modification of the powertrain and tuning of the target noise in the early stages of vehicle development. In another TPA study, [PERSON] et al. [11] calculated the contribution of structure-borne noise from the rear final drive to the sound pressure on the driver's ear. [PERSON] et al. [12] proposed an operational TPA (OTPA) for structure-borne noise analysis. The low-frequency vibrations of steering wheels have been reduced by a systematic analysis based on classical TPA [13]. TPA can accurately and effectively determine the composition of the structural vibration transfer path and its impact on the interior noise [14]. The TPA and TPS methods have been increasingly applied to acoustic analyses of EVs [15, 16, 17, 18, 19, 20, 21]. For example, TPA has analyzed the contribution of panel noise to an EV [15]. [PERSON] et al. [16] investigated the noise contribution to an EV through experimental measurements and a synthetic method based on TPA principles. [PERSON] et al. [17] evaluated the influence of harmonic-order noise introduced by different components of the EV. [PERSON] et al. [18] measured and analyzed the transfer path of acoustic phenomena in the driver cabin of a battery electric vehicle using TPA, and [PERSON] et al. [19] accurately predicted the interior electromagnetic noise of an EV by combining TPA with motor electromagnetic vibration simulations. Meanwhile, the OPTA method has effectively improved the cabin noise in an electric minivan by separating the noise contributions from the tires, powertrain, and wind [20]. OTPA infers the effects of the sound sources on the driver's ear from operational measurements. [PERSON] et al. [21] investigated the noise component contribution in EV by new separation technology. Road noise and wind noise influence increase and become a significance factor for EV. The SQ of ICEVs has a clear and simple research objective. The SQ of an ICEV is predicted and controlled by the technical development of the main noise source (in this case, the ICE power system). As the SQ characteristics of EVs significantly differ from those of ICEVs, the NVH studies will largely differ between PEVs and ICEVs. Therefore, a new sound evaluation method is needed for PEVs. Whether the TPA research method of conventional ICEVs can be quickly applied to the acoustic design of PEVs is not certain.