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The paper analyzes the technological features of hydrogen fuel cell vehicles, describes the changes that hydrogen fuel cell vehicles will bring to the automobile industry and the marketing modes, and proposes a brand-new marketing mode of “automobile supermarket”. It also introduces the opportunities and challenges that fuel cell technology will bring to the world energy technology, and puts forward a concept of “hydrogen energy network” to push the mutual development of both hydrogen fuel cell vehicles and hydrogen energy industry.

Operating level of a metal-belt CVT mainly rest with the ECU. Conventional control strategies which were obtained from tests or PID controller can not correspond to the driver’s intention or provide various driving environments. It is considered that control targets of metal-belt CVT could be distinguished by a speed ratio, line pressure and starting element till now. Running performance of automobile with a CVT mainly depends on the speed ratio control. An adapted fuzzy logic ratio control algorithm is suggested and optimized. A throttle position and its changing rate will be inputs of the FLC to meet the driver’s intention and make the intelligent control come true. A fuzzy logic line pressure control algorithm is also suggested and optimized corresponding to the complicated high line pressure control.

Hydraulic retarder braking torque is needed to be controlled. Retarder braking torque refers to oil volume in retarder chamber, thus the key of braking torque control is oil charging & discharging control. The hydraulic oil charging & discharging system should have fast accurate response and provide enough flow rate. To achieve the requirement, the system is often complicated, many parameters need repeated test to determine, which increases the R&D cost and extends the research cycle. This paper tries to find a time-efficient research method on hydraulic retarder oil charging & discharging control system. The complete system is divided into some parts and every part is analyzed respectively based on mechanical theory and hydraulic theory. To build the precise model of all parts, the AMESim software is used.

Speed ratio and clamping force are two of the metal-belt CVT control targets. Conventional control strategies can not correspond to the driver's intention or provide various driving environment. A fuzzy logic ratio control algorithm and a fuzzy logic clamping force control algorithm for a metal-belt CVT are proposed. Nevertheless, high-quality fuzzy control rule base and factors of FLC are difficult to gain because repeated tests and experts' experience are needed. Therefore, genetic algorithm (GA) is introduced to optimize the fuzzy control algorithms. Using the optimized fuzzy control algorithms, Metal-belt CVT control simulations were implemented. The results show that a faster response and better robustness can be gained when compared with those of the PID control.