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- W2187307564 abstract "linear model of a vehicle engine and drivetrain. A hybrid approach ha: been adopted which combines 30th physical modeling and parameter optimization using gen-tic algorithm (GA) search techniques. The resulting models which cover a range of operating conditions have allowed the sensitivity to variation of key pari.meters to be assessed and have been used to help optimize the o.erall response of the vehicle drivetrain. A comparison has bem made between the GA search and a gradient based method M hich highlights the intelligent nature of the fornier appro ich. W out to identify a nonBackground Advan:es that have been made to iniprovc. the economy and emis> ions of powertrains have increased efficiencies and lowcred frictional losses. bringing reducd powertrain daniping and a greater sensitivity to eling work carried out during an investigation into the tuning and control of driveline torsional oscillation. The model is based on a transfer function and state space description that is simple, but which allows inclusion of nonlinear effects associated, for example, with the operation of the clutch and with transmission backlash. The model has been used to help in identifying important component characteristics to adjust the stiffness and damping of the drive system. Test data for the work was acquired from a development vehicle and this comprised measurements of engine crank velocity, throttle position, vehicle speed, and acceleration. Maneuvers were carried out at a variety of engine and vehicle speeds, and in low gear ratios, to stimulate longitudinal oscillation." @default.
- W2187307564 created "2016-06-24" @default.
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- W2187307564 date "1993-01-01" @default.
- W2187307564 modified "2023-09-27" @default.
- W2187307564 title "AIpplying Genetic Search Techniques to Drivetrain Modeling" @default.
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