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Because variable transmissions usually operate at optimal gear ratios, they allow for efficient switching between gas and electric power sources.
When driven in that mode, the car's G-AI control system automatically selects the optimal gear ratio and downshift pattern in response to the G forces generated.
The resulting optimal gear ratio is compared to that obtained from the conventional inertia matching method.
Optimal gear design consists of determining its proper size, geometry, material, manufacturing processes and process parameters.
The results of simulations indicate that the optimal gear ratio can greatly reduce the amount of the dissipated energy.
To ensure an optimal gear shifting strategy with best fuel economy for a stepped automatic transmission, the controller should be designed to meet the challenge of lacking of a feedback sensor to measure the relevant variables.
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It is shown that the described optimization strategy allows finding optimal micro-geometry modifications of tooth profile that enable significant improvements in all the observed performance indices with respect to the unmodified gear design, as confirmed by detailed numerical simulations of the optimal gears.
These principles predict an optimal angular position for the ATP-binding transition close to the experimental value; an inverse relation between the optimal gearing ratio and the proton motive force (pmf); optimal operation at an inflection point in the curve of ATP synthesis rate versus pmf, enabling rapid metabolic control; and a high optimal free energy conversion efficiency.
Catches ha−1 of mostly retained (commercially important) large brachyurans and cephalopods were maintained, but penaeid catches were reduced in the W trawl (by at least 33%), which was mostly attributed to less than optimal ground-gear contact.
The works include power train specification design, mechanism and controller design for the clutchless AMT, optimal transmissions gear-shifting strategy design, and finally, power split strategy design for the 4WD in terms of wheel slip ratio control.
The gearbox design process can be improved by using genetic algorithm to determine the optimal values of gear pair parameters.
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