Evaluation of Dynamic Load Coming on E-Driveline Due to Bump and Study its Effect on Motor Mountings and Battery Position

<div class="section abstract"><div class="htmlview paragraph">During the development of E-Driveline, it observed that loading failure encountered with On-highway vehicle’s E-Drivelines has increased in comparison with traditional driveline. The major cause of these failures is motor and battery reaction loads acting on driveline in electric vehicles. The main source of load generation is acute dynamic reaction coming from road conditions i.e., bumps, potholes, ditch, uneven surfaces, and it transferred to motor or batteries through the E-Driveline. The uneven distribution of motor and battery loads in vehicle will amplify the dynamic reactions which may lead to severe failures. It will be useful if we predict the dynamic loads in early design and simulation stage for accurate solution.</div><div class="htmlview paragraph">This work is based on development of multi body dynamic modeling and simulation approach to predict loads coming on to E-Driveline due to road conditions and correlate it with test setup of actual vehicle running on these road conditions. After the correlation, studied its effect on motor mountings and battery position to achieve the optimum load transfer with the help of dynamic simulations. Motor mounting position is optimized to get minimum displacement of motor block by iterating bushing stiffness and location. Battery position is adjusted based on load distribution of Front Axle weight (FAW), Rear Axle weight (RAW) and location of center of gravity (CG).</div><div class="htmlview paragraph">The present work contains simplified multi body dynamic full vehicle model with E-Driveline developed in dynamic software, bump geometry road profile with actual field measurements developed with the help of software tool. Test Setup is mounted on vehicle with load and accelerations sensor at different positions on E-Driveline for test data measurements. Simulations are carried out with different speeds same as test condition to correlate with measured test data. Based on correlated data this methodology will be useful for predicating G-Factors, dynamic loads for different E-Driveline variants.</div></div>