Electric Drive Units (EDUs) are at the heart of modern electric vehicles, combining the electric motor and transmission into a single, compact system. These units are crucial for achieving the efficiency, performance, and reliability expected in electric cars.
A key challenge in the design of EDUs is ensuring effective lubrication. Proper lubrication minimizes friction, reduces wear on components, and helps dissipate heat, all of which are critical for maintaining the longevity and efficiency of the system. Additionally, as EDUs operate at high speeds and under varying loads, optimizing lubrication becomes essential for achieving peak performance while meeting stringent durability requirements.
This simulation case explores the behavior of lubrication within an EDU, focusing on how oil is distributed and interacts with critical components.
Objective of Part I: Simulating Lubricant Flow in the Rotor
In this first phase of the Electric Drive Unit (EDU) simulation study, we focus exclusively on the rotor, isolating it from the rest of the system. The primary objective is to estimate the lubricant flow distribution through the various channels within the rotor.
The lubricant enters the simulation domain through the central shaft of the rotor and is distributed from there into eight small channels located at both ends of the shaft. These channels guide the lubricant toward specific regions outside the rotor.
The aim of this simulation is to calculate the percentage of the main lubricant flow that splits and enters each of the eight channels. Understanding this distribution is crucial for optimizing the channel design to achieve uniform lubrication.
Case discription
The general setup of the simulation is depicted in the image below. The lubricant enters the domain through an inlet located in the central shaft, with a volume flow rate of 12 liters per minute. The simulation has a base particle size of 0.06 mm.
To ensure accurate resolution of the flow dynamics near the small channels, refinement regions are applied around these areas. Within these regions, the particle size is reduced to 0.03 mm, enhancing the precision of the simulation in capturing detailed flow characteristics.
Each of the eight channels is equipped with sample windows that measure the flow rate passing through them. These measurements provide critical data for evaluating how the lubricant flow is distributed across the channels.
Rotor starts at 0 RPM and ramps up to 2000 RPM within 0.5 seconds.
Result
The first image in this section illustrates the particle size distribution within the rotor. As shown, the particles are reduced to half their size in the predefined refinement regions, enabling them to flow seamlessly into the smaller channels. After passing through these regions, the particles merge back together, effectively reducing the overall particle count. This approach significantly lowers computational effort while maintaining simulation accuracy.
The video below provides a dynamic visualization of the simulation results. It shows the filling of the shaft and the side channels, the rotor ramp-up, and the resulting velocity distribution of the fluid within the system.
The two diagrams below illustrate the development of the flow rate through the sample windows over time. The naming convention, such as “Sample 1 / Sample 1-1,” refers to opposing channels. Samples 1 and 2 are located on the left side, closer to the inlet, while Samples 3 and 4 correspond to the channels on the right side, further from the inlet.
As a result, Samples 1 and 2 detect incoming fluid earlier, a behavior that is also visible in the video above. All eight channels reach their final flow rate nearly simultaneously, around 0.4 seconds. From this point onward, the flow rates remain relatively stable, indicating that the simulation has achieved a steady state and was run for a sufficient duration.
The dashed lines in the diagrams represent the average flow rates for each sample over the last 0.25 seconds of the simulation (from 1.0 to 1.25 seconds):
- Sample 1: 1.15 L/min
- Sample 2: 1.80 L/min
- Sample 3: 1.25 L/min
- Sample 4: 1.80 L/min
These results will be taken as Inputs Data for Part II of the EDU simulation where the whole EDU is simulated:
