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For the parallel hybrid electric vehicles in which there are one engine and one motor, and the motor is located before the transmission, the motor torque is added as a new parameter to develop a new shift strategy for automated manual transmissions. The design rule of the shift strategy is to pursue a better fuel economy without sacrificing performance of the vehicle. Upshift strategies in four driving modes and downshift strategies in driving mode and in braking mode are discussed in detail respectively. Simulations show that the new three-parameter shift strategy is able to save fuel consumption in driving mode and regenerate more energy in braking mode.

Logic threshold control algorithm for parallel hybrid electric power train is presented systematically, in which engine operation points are limited within higher efficient area by logic threshold control algorithm targeting fuel economy. The off-line simulation model of parallel HEV power train is developed which includes sub-models of logic threshold control system and controlled objective (such as engine, electric motor, battery pack and so on). The debug and validation of logic threshold control algorithm is completed on developed modular test facility. The results show that the simple and practical logic threshold control algorithm can effectively limited engine operation points and much more fuel economy can be achieved than that of conventional ICE power train.

Utilizing the developed off-line simulation model of series hybrid power train the study on the influence of components' parameters on acceleration performance and fuel economy of transit bus is completed. Based on these the guideline strategies of parametric design of series hybrid power train for transit bus are brought forward in this paper. Given the condition of propulsion requirement the parametric design for this transit bus are performed targeting minimizing fuel consumption. It is conclusion that the appropriate components' parameters determined by means of parametric design can make series hybrid transit bus achieve much better acceleration performance and much lower fuel equivalent consumption than that of baseline transit bus.

Developed control algorithm for series hybrid electric power train is presented systematically, which keeps engine operation points on the locus of highest efficiency torque/speed points using a lookup table defined by engine power and speed. The off-line simulation model of series hybrid power train is developed which includes sub-models of control system and controlled objective (such as engine, motor, battery pack and so on). The debug and validation of control algorithm is performed on developed modular test facility. The results show that developed control algorithm can effectively keep engine operating on the locus of high efficiency points and much more fuel economy can be achieved than that of conventional ICE power train, meanwhile battery SOC can be maintained within reasonable level without charging outside during cycles.

In concept design and prototype development of parallel hybrid power train for transit bus one of the main concerns is to determine the appropriate parameters of power train components. Utilizing the developed off-line simulation model of parallel hybrid power train the study on the influence of components' parameters on acceleration performance and fuel economy of transit bus is completed. Based on these the guideline strategies of parametric design of parallel hybrid power train for transit bus are brought forward in this paper. Given the condition of propulsion requirement the parametric design for this transit bus are performed targeting minimizing fuel consumption. It is conclusion that the appropriate components' parameters determined by means of parametric design can make parallel hybrid transit bus achieve much better acceleration performance and much lower fuel equivalent consumption than that of baseline transit bus.

In order to achieve the best shifting performance, the traditional hybrid vehicles shift schedule design based on multi-parameter shift schedule, these shift methods can improve fuel economy and acceleration performance to a certain extent. but it is difficult to obtain the optimal performance because it is a compromise between power and economy shift schedule. This paper provides adaptive shift strategy based on driving style recognition to select the optimal shift schedule, thereby improving the dynamic performance of the vehicle as well as reduced fuel consumption.

Developed control algorithm of series power train for fuel cell transit bus is presented systematically, which keeps fuel cell pack's operation points on the locus of highest efficiency. The off-line simulation model of series power train for fuel cell transit bus is developed which includes sub-models of control system and controlled objective (such as fuel cell pack, motor, battery pack and so on). The debug and validation of control algorithm is performed on developed modular test facility. The results show that developed control algorithm can effectively keep fuel cell pack's operating on the locus of high efficiency points and much more fuel economy can be achieved than that of conventional ICE power train, meanwhile battery SOC can be maintained within reasonable level without charging outside during cycles.

Utilizing the developed off-line simulation model of series power train for fuel cell transit bus, the study on the influence of components' parameters on acceleration performance and fuel economy of transit bus is completed. Based on these the guideline strategies of parametric design of series power train for fuel cell transit bus are brought forward in this paper. Given the condition of propulsion requirement the parametric design for this transit bus is performed targeting minimizing fuel consumption. It is conclusion that the appropriate components' parameters determined by means of parametric design can make fuel cell transit bus achieve much better acceleration performance and much lower fuel equivalent consumption than that of baseline transit bus.

In concept design and prototype development of hybrid power train with ISG (Integration of Starter and Generator) for transit bus one of the main concerns is to determine the appropriate parameters of power train components. Utilizing the developed off-line simulation model of hybrid power train with ISG the study on the influence of components' parameters on acceleration performance and fuel economy of transit bus is completed. Based on these the guideline strategies of parametric design of parallel hybrid power train for transit bus are brought forward in this paper. Given the condition of propulsion requirement the parametric design for this transit bus is performed targeting minimizing fuel consumption. It is conclusion that the appropriate components' parameters determined by means of parametric design can make hybrid transit bus with ISG achieve much better acceleration performance and much lower fuel equivalent consumption than that of baseline transit bus.

A practical configuration of the power train for the parallel hybrid electric vehicle (HEV) is presented in this paper. The parameters of the power unit (included engine, motor, battery) that must be considered and determined during parallel HEV designing are calculated and discussed in details according to the vehicle requirements for maximum speed, acceleration time, maximum grade ability, emission, fuel efficiency. The parameters of the battery are determined by calculation and the measures that will be taken in design are also discussed in this paper. In cycles it must be insured that the consumed energy and absorbed energy through regenerative braking are balance. Thus the battery pack will never have to recharge from wall plug, the range is as long as conventional vehicle. The ratio of torque-combination device, transmission and the final drive gear is optimized and determined respectively based on the vehicle criteria of traction performance and the fuel economy.

The traditional vehicle design methods of hybrid electric vehicles are based on the rule-based control strategy, which often adopt the trial and error methods and the model-based numerical optimization methods. But these methods require a large number of repeated tests and a longer-term development cycle. In this paper, approximately the global optimization algorithm was used in control parameters designing through rational design of the penalty weights of objective function. But the optimized parameters apply only to vehicles that operating in the special drive cycle to get better fuel economy. Therefore, a drive cycle recognition algorithm was proposed to identify types of drive cycles in real-time, then an off-line genetic algorithm was adopted to acquire the optimization of control parameters under the various drive cycles, through drive cycle recognition results to choose the best control parameters.