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Prediction at the drawing stage by implementing CAE with its main feature of the finite element method is effective also for early detection of problems of strength, rigidity, and vibration in the development of motorcycles, and makes a significant contribution to the improved developmental efficiency. Accuracy of simulation is determined by precise analysis models and input conditions analogous to actual tests. Actual tests have been replaced by functional tests of individual unitary components as far as possible to save time. Load conditions due to engine vibration and various road surface reactions, as well as restrictive conditions, are classified by specifications of business and sports, and are used to prepare a database.

Since the operation of the powertrain system and the engine speed and torque are determined in the ECU in hybrid vehicles, control parameters in these vehicles are more sensitive to a variety of performance factors than those employed in conventional vehicles. The three performance factors acceleration performance, NVH and fuel consumption in particular are in a tradeoff relationship, the calibration of control parameters in order to satisfy these performance targets entail considerable development costs. Given this, it is possible to increase the efficiency of hybrid vehicle development by determining Pareto design solutions for the three performance factors via multi-objective optimization using CAE, and selecting target performance and control parameters based on these Pareto design solutions.