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The conventional aftertreatment systems to meet the stringent ULEV-II emission regulation are usually composed of warm-up catalytic converter (WCC) and underfloor catalytic converter (UCC). However, those systems bring high cost, high back pressure, the limit of engine room for package design, and other side effects.[4] The new optimized system needs to solve these problems and to meet ULEV-II emission regulation efficiently. There are many technologies and design parameters in exhaust catalytic converter systems; exhaust manifold structure[9], exhaust gas flow distribution, location of catalytic converter, PM coating technologies[1], substrate characteristics, and volume of catalysts. It is a key factor to make a optimized robust system with those parameters and technologies described. The new optimized exhaust and Integrated Close-coupled Catalytic Converter (ICCC) system can meet ULEV-II regulation and can solve those problems of conventional system by a robust design.

A CVT ratio control algorithm is proposed to improve the engine performance by considering the powertrain response lag. In the CVT powertrain, there exists a response lag, which results from the throttle response, engine torque dynamics, CVT filling time, CVT shift dynamics, and the drive shaft dynamics including the tire. This response lag causes the deviation of the engine operation from the optimal operation line for the minimum fuel consumption. In the CVT ratio control algorithm suggested in this paper, the desired CVT speed ratio is modified from the vehicle velocity, which is estimated after the time delay due to the powertrain response lag. In addition, the acceleration map is constructed to estimate the vehicle acceleration from the throttle pedal position and the CVT ratio. Using the CVT ratio control algorithm and the acceleration map, vehicle performance simulations and experiments are performed to evaluate the engine performance and fuel economy.

In this study, a co-operative regenerative braking control algorithm was developed for an electric vehicle (EV) equipped with an electronic wedge brake (EWB) for its front wheels and an electronic mechanical brake (EMB) for its rear wheels. The co-operative regenerative braking control algorithm was designed considering the road friction characteristic to increase the recuperation energy while avoiding wheel lock. A powertrain model of an EV composed of a motor, and batteries and a MATLAB model of the control algorithm were also developed. They were linked to the CarSim model of the vehicle under study to develop an EV simulator. The EMB and EWB were modeled with an actuator, screw, and wedge to develop an EMB and EWB simulator. A co-simulator for an EV equipped with an EWB for the front wheels and an EMB for the rear wheels was fabricated, composed of the EV and the EMB and EWB simulator.

A regenerative braking algorithm is proposed to make maximum use of regenerative brake for improvement of fuel consumption. In the regenerative braking algorithm, the regenerative torque is determined by considering the motor capacity, battery SOC and vehicle velocity. The regenerative braking force is calculated from the brake control unit by comparing the demanded brake force(torque) and the motor torque available. The wheel pressure that is reduced by the amount of the regenerative braking force is supplied form the hydraulic brake module. In addition, CVT speed ratio control algorithm is suggested during the braking. The optimal operation line is obtained to operate the motor in the most efficient region. It is found from the simulation that the regenerative braking algorithm including the CVT ratio control provides improved fuel economy as much as 4 percent for federal urban driving schedule.

A fuzzy logic ratio control algorithm for a metal belt CVT is suggested considering the on-off characteristics of the ratio control valve and the nonlinear characteristics of the CVT shift dynamics. In the fuzzy logic, variable computation time for the error of the ratio and the rate of the error is suggested depending on the velocity of the rate of the CVT ratio. Experimental results show that a desired speed ratio can be achieved at a steady state by the fuzzy logic in spite of the fluctuating primary pressure. In addition, it was found that a faster response and better robustness can be obtained when compared with those of the PID control. It is expected that the ratio control algorithm suggested in this study can be implemented in a prototype CVT.

A new fuel economy optimization method for parallel hybrid electric vehicles with continuously variable transmission( CVT) is proposed in this paper. The method maximizes overall system efficiency while meeting desired performances. Firstly, effective specific fuel consumption (ESFC) is defined as effectively consumed fuel per output power-hour from a hybrid propulsion system, in which battery output power is transformed into an equivalent amount of fuel. Hence, hybrid optimal operation line(HOOL) is derived based on ESFC as optimal operation line(OOL) is found based on specific fuel consumption( SFC) in a conventional internal combustion engine(ICE) vehicle with CVT. From HOOL, optimal combinations of control variables, CVT gear ratio, motor torque and engine throttle, are obtained versus vehicle velocity, battery state of charge and required power. A simulation study with the proposed optimization method is performed to prove its validity.