Dynamic additional loads influencing the fatigue life of gears in an electric vehicle transmission
G.Belingardi, V.Cuffaro, F.Cura, Frattura e Integrita Strutturale, 2014, Issue 30, pp 469-477.
Abstract
In recent years the implementation of the electric engine in the automotive industries has been increasingly marked. The speed of the electric motors is much higher than the combustion engine ones, bringing transmission gears to be subjected to high dynamic loads. For this reason the dynamic effects on fatigue life of these components have be taken into account in a more careful way respect to what is done with the usual gears. In the present work the overload effects due to both speed and meshing in a gear couple of an electric vehicle transmission have been analyzed. The electric vehicle is designed for urban people mobility and presents all the requirements to be certified as M1 vehicle (a weight less than 600 kg and a maximum speed more than 90 Km/h). To investigate the overload effects of teeth in contact, the reference gear design Standards (ISO 6336) introduce a specific multiplicative factor to the applied load called Internal Dynamic Factor (Kv). Aim of this work is to evaluate how dynamic overloads may influence the fatigue life of the above quoted gears in term of durability. To this goal, Kv values have been calculated by means of the analytical equations (ISO 6336 Methods B and C) and then they have been compared with the results coming from multibody simulations, involving full rigid and rigid-flexible models.
How Multibody Dynamics Simulation Technology is Used
RecurDyn was used to simulate the dynamic behavior of an automotive transmission for an electric vehicle. This simulation provided the necessary information to obtain the Internal Dynamic Factor. The gears were simulated first as rigid bodies and second as flexible rims and rigid webs. In this case both simulations provided similar answers with the flexible approach having a longer simulation time. The fatigue life of the gears could be evaluated to determine if design changes should be made to improve life based upon these results.
