Electrified Drive-Unit Parametric Mechanical-Loss Model Development and Calibration 2019-01-1298
As the automotive industry vies to meet progressively stringent global CO2 regulations in a cost-effective manner, the electrified drive system cost and losses must be reduced. To this end, a parametric Drive Unit (DU) mechanical loss model was developed to aid in the design and development of electrified propulsion systems, where the total propulsion system cost and DU losses can be directly linked (e.g., HEV motor/inverter/engine content, or BEV battery size).
Many DUs for electrified propulsion systems are relatively “simple” drive systems, consisting of gears, bearings, shafts, lip seals, and an electric motor(s), but without clutches, high-pressure lube systems, or chains/belts as found in conventional automatic transmissions. The DU loss model described in this paper studies these simple DUs, with the mechanical losses dissected into 10 loss components.
Analysis was conducted at the vehicle level to assess the relative loss contributions of the DU, motors, engine, etc. for the entire vehicle-propulsion system to show the DU loss contribution to the total system. The DU loss model was used to deconstruct the total DU mechanical loss into subcomponents of speed-dependent and load-dependent losses. For each loss component, standard loss model equations were modified, or new equations were created, and calibrated based on loss data/trends of component-level bench tests, supplier data, and DU-level tests. Particular emphasis was placed on the load-dependent components of the gear and bearing losses, as a function of load and speed, as they can represent a large portion of the total DU loss. DU-level tests were conducted at various positive and negative (regen) loads, speeds, fluid type and temperature and sump-fill level. The model calibration methodology is described, where the calibration of the individual component models was iterated, so that a universal set of loss model calibrations produce loss results that closely match the test DU losses at the various operating conditions.
Goro Tamai, Sairanga Palaparthy, Bruce Wang, Ralph Ilunga