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The city buses start and stop frequently, therefore significant amount of kinetic energy is wasted on friction plates. In order to retrieve this amount of energy, various feasible and efficient energy storage systems have been suggested by researchers to reuse the energy to improve the efficiency of the city bus. Due to small size, high energy density, cleanliness and easiness to absorb/reuse the energy, the storage system of flywheel is hopeful to be coming into wide use. In this paper, a dynamic model is analyzed to study the characteristics of the system using time series. Finally, comparison between simulation and experiment is given.

In this paper,the flywheel is considered to be linear elastic composition in accordance with its operating characteristic, mechanical and mathematical model are presented,the finite element method is employed to carry out the numerical analysis of steady and unsteady stresses within the high speed flywheel in the regenerative braking system of a city bus,and these provide the basis foŕ its structural modification and further rational design.

In this paper the nonlinear system identification theory and method using neural networks are presented, the multilayer feedforward networks employed, the backpropagation learning algorithm proposed. The inputs of the networks are consisted of angular velocity and throttle angle, and outputs torque of the engine, finally the comparision of simulation result with that of experiment and other results that embody the effect of system identification are given. Relative studies revealed that the nonlinear system identification for the engine of automated automobiles using neural networks can be effective.