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Recently, the market share of electric vehicles is becoming increasingly obvious. It is expected that electric vehicles are quieter than fuel vehicles. Actually, without the cover of low-frequency engine noise, the high-frequency noise of electric vehicles is more prominent, which seriously affect the perceived sound quality. The present work is related tonal noise resulted from electric drive system (EDS), which is one of the fundamental noise sources for battery electric vehicle (BEV). The dominant noise sources observed in the vehicle interior are 26th and 36th orders for reducer and drive motor separately. Poor vibration isolation of right mounting system is the fundamental cause identification of EDS noise which has been investigated with objective measurements and simulation tools. Dynamic stiffness analysis is carried out to optimize the passive bracket. An engineering solution is implemented to enhance bracket to improve resonance effect.

This paper describes a simplified model to identify sprung mass using golden section method, the model treats the unsprung mass vertical acceleration as input and the sprung mass vertical acceleration as output, which can avoid the nonlinear influence of trye. Unsprung mass can be also calculated by axle load and the identified sprung mass. This study carries out road test on the vehicle ride comfort and takes a scheme that the group of 20 km/h is used to identify sprung mass and the group of 80 km/h is used to verify the identification result. The similarity of the results from the simulation and experiments performed are, for the sprung mass, 98.59%. A conclusion can be drawn that the simple method to measure the sprung mass in the suspension systems in used vehicles, such as the vehicle shown here, is useful, simple and has sufficient precision.

Vehicle Thermal Management System (VTMS) is a cross-cutting technology that directly or indirectly affects engine performance, fuel economy, safety and reliability, driver/passenger comfort, emissions. This paper presents a novel methodology to investigate VTMS based on Modelica language. A detailed VTMS platform including engine cooling system, lubrication system, powertrain system, intake and exhaust system, HVAC system is built, which can predict the steady and transient operating conditions. Comparisons made between the measured and calculated results show good correlation and approve the forecast capability for VTMS. Through the platform a sensitivity analysis is presented for basic design variables and provides the foundation for the design and matching of VTMS. Modelica simulation language, which can be efficiently used to investigate multi-domain problems, was used to model and simulate VTMS.