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A validated model which attributes fuel consumption to 11 components of a vehicle's energy loss, has been applied to investigate the benefits from improvements in design parameters which can reduce fuel use. Sensitivity analysis of a large, family sized car, gives the ranked order of design variables for improving fuel consumption as: vehicle mass, idle fuel rate or engine friction (or both) and rolling resistance for urban driving. Amongst the remaining parameters aerodynamic drag is lowly ranked but, in highway driving, it ranks first along with vehicle mass and rolling resistance, thus indicating that the proportion of urban to highway driving, which will vary from country to country is important. Driving conditions should be optimised along with vehicle design for best energy conservation and greenhouse gas mitigation.

New emissions regulations of light-duty vehicles (China 6) will be implemented in China from July 1, 2020. This standard includes two stages, China 6a and China 6(b), in which the PM limits of 4.5 mg/km and 3.0 mg/km are introduced respectively; the PN limit is set to be 6×1011 #/km for both stages. The WLTC testing cycle will be implemented in China 6 regulation as well. In this study a light-duty vehicle satisfying China 6(b) emission standards was developed by improving the engine raw emissions, optimizing the calibration and adding a coated GPF to the after-treatment system. The impacts of ash content and consumption of engine oil and the fast ash accumulation to vehicle emissions and backpressure were analyzed through dynamometer testing. The vehicle after-treatment system was then designed and developed to meet China 6(b) emission standards. The characteristics of soot accumulated through mimicking routine driving under cold environments were tested.

In modern car, to reduce car deadweight, lightweight technology is widely used; and to improve comfortable and handling performance, many rubber bushings installed between car body and suspension. These parts have difference characteristics during car running at high speed comparing these at static state. Accounting the suspension performance has a decisive influence on a car, the flexible parts should be taken into account in the suspension/steering system simulation model. As a deviant phenomenon, the steering wheel shimmy affects the suspension's dynamic characteristics greatly. To analysis this abnormal running state, the front wheel bounce tracks were figured out by using different front suspension model. The flexible parts installed in suspension are idealized respectively as rigid poles, flexible beams or forces, hence, the rigid suspension analytical model and the rigid-elastic suspension model analytical were built respectively.

The global adaptive cruise control (ACC) market is expected to witness a compound annual growth rate of 18.3% during the forecast period to reach $15,290 million by 2023 [1]. The driver uses an ACC system to reduce the driving burden and improve safety. The ACC mode in a car is fixed, but different drivers have different driving habits. This paper will verify this through experiments and divide drivers into three categories according to the drivers’ driving habits. Therefore, we will design a personalized ACC, wherein an ACC system, under the same working conditions, can have different acceleration and deceleration to meet the needs of different types of drivers. Therefore, this paper collects driver data, analyzes model data and identifies its parameters, and finally verifies the different effects of personalized ACC through simulation.