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Technical Paper

Development of an Integrated Electrified Powertrain for a Newly Developed Electric Vehicle

2013-04-08
2013-01-1759
This paper describes a newly developed electrified powertrain that incorporates various energy-saving improvements and is intended for use on a 2013 model year EV. Based on a 2011 model year EV that was specifically designed and engineered as a mass-produced EV, this powertrain integrates the traction motor, inverter and charging unit to achieve a smaller, lighter package for expanding application to more vehicles. Integration of the motor and inverter in particular reduced the part count for enhanced assembly ease, in addition to reducing heat transfer, noise and vibration. The specific features described in the paper are the three points below. Improving the layout of the inverter parts in order to downsize and integrate the inverter with the motor. Reducing the transfer of heat from the motor to the inverter. Reducing the excitation forces of the motor and optimizing the inverter for noise and vibration.
Technical Paper

Using Multiple Regression Analysis to Estimate the Contributions of Engine Radiated Noise Components

2000-06-12
2000-05-0292
The respective contributions of combustion noise, mechanical noise, noise attributed to the fuel injection system and other engine noise components must be identified in order to devise effective measures for reducing diesel engine noise. This paper describes a method for estimating the contributions of engine noise components using multiple regression analysis. With this method, the engine noise level is regarded as a criterion variable and the cylinder pressure level and several parameters are examined as explanatory variables. The accuracy of this method has been confirmed by comparing the results with experimental data. It was found that, by selecting adequate parameters as explanatory variables according to the type of fuel injection system used, the respective contributions of combustion noise, mechanical noise and fuel-injection noise estimated by multiple regression analysis agreed with the experimental data.
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