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The Real Driving Emissions (RDE) test method has been introduced after 2017 to regulate the vehicle emissions in real-world driving situations by means of on-board emissions measurements. This paper aims to estimate the detailed on-board gaseous emissions from a light-duty direct-injection gasoline vehicle simultaneously using both portable emissions measurement system (PEMS) and sensor-based emissions measurement system (SEMS). Test route is typical urban route and tests environment factors followed the RDE regulation. Carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), and ammonia (NH3) emissions were analyzed according to cold start once and followed by hot start conditions. The mass emissions of gas components were calculated based on the exhaust flowrate obtained from OBD parameters, NH3 emission was calculated based on NO sensor’s data. Two drivers participated in the tests and their emissions difference has been compared.

To investigate the ignition process in a diesel spray, the ignition in a transient fuel spray is analyzed numerically by a discrete droplet spray model (DDM) coupled with the Shell kinetics model at various operating conditions. Predicted results show that the fuel mixture injected at the start of injection, which travels along midway between the spray axis and the spray periphery, contributes heavily to the first ignition in a spray. The equivalence ratio and temperature of the first ignited mixture are kept nearly constant until the start of hot ignition. The temperature of the first ignited mixture is kept at a constant value of higher temperature than the thermodynamic equilibrium temperature of the mixture before the hot ignition starts. The equivalence ratio of the first ignited mixture is around 1.6 at initial gas temperatures between 750 K and 850 K.

Two kinds of active control systems, using neural networks (NN), are presented for realizing optimal driving motion of four wheel steer (4WS) cars. The first system is based on the assumption that the car is simplified as a linear two wheel bycycle model, and that the friction force between tire and road surface is represented by Fiala's nonlinear model. The nonlinear relation between the slip angle of tire and the cornering force is expressed with NN. A model-following type control strategy is adopted in the first system, with both the feedforward and feedback gains for the control of the rear wheel steering angle adaptively determined with NN according to change of front wheel steering angle. The second system is based on the assumption that both the dynamical characteristics of the car and the tire friction force are nonlinear. The nonlinear dynamical characteristics of the car and the friction force are identified with NN, using the measured data of an actual car.