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This paper is concerned with the design of a newcontroller for active suspension system. The model isconsidered as a quarter-car. The presented controller dependson the fuzzy technique and NARMA-L2 linearizationalgorithm. The compensation system that added by the fuzzyrules improves the performance of the controller, while theneural network produces the required control signal. The newcontroller can achieve an improvement of the ride comfortwith a reasonable value of power consumption. Themathematical analysis of the mechanical power used by themodel is focused on the average and the RMS of the powersupplied to the system, regardless of the frequency content ofthe vibration signal. The simulation results which are verifiedby a practical examples of road profiles, demonstrate theefficacy of the proposed controller.

In this paper, a statistical method is employed to develop a driving cycle for Basrah city and to find out the factor score a nd the Euclidean distance analysis by the Statistical Package for the Social Sciences (SPSS). A simple electronic system is built to construct the driving cycle, the system considered a microcontroller and a GPS sensor connected to a PC through a simple C++ code. The development of the proposed driving cycle represents the first model driving cycle in the city of Basra. The advisor software package is used to investigate the economic performance of the internal combustion engine based on HC, CO, and NOx exhaust emissions. It was found that the obtained driving cycle is significantly different than the other driving cycles in terms of exhaust emissions and fuel consumption and within the expected range of emissions. The developed driving cycle model obtained is a representative delicate estimation of the exhaust emissions and fuel consumption, and will be utilized for future work to obtain a good performance of the hybrid electric vehicles.

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