Keywords

1 Introduction

1.1 Motivation

Increasingly stringent emission standards and the growing shift towards electric mobility are driving automotive manufacturers to focus on optimizing the efficiency of individual components within the powertrain. This also includes wheel bearings, crucial for supporting the rotational movement of wheels and transferring associated forces to the vehicle body. The resulting losses significantly affect the powertrain efficiency, leading to a reduction in overall efficiency [1, 2]. The presented methodology enables the determination of losses in real-world driving conditions and helps to identify deviations from homologation-relevant vehicle test benches. This is particularly important because analyzing the loss characteristics of wheel bearings in real-world vehicle operation is complex and expensive.

1.2 Test Bench Setup

The schematic representation of the component test bench for determining friction losses of wheel bearings is depicted in Fig. 1. The bearing is mounted using two adapters within a climate chamber to maintain consistent ambient temperature conditions. An electric motor with dynamic control capabilities drives the bearing, while a load unit applies axial and radial loads. A sensor setup within the illustrated measurement unit captures the resulting friction losses of the measured bearing. Furthermore, various parameters, including ambient temperature, bearing temperature, and rotational speed, are recorded throughout the test.

Fig. 1.
figure 1

Test bench setup to determine the friction losses of wheel bearings.

2 Methodology

The methodology aims to assess the losses experienced by wheel bearings under real-world driving conditions and identify deviations from homologation-relevant complete vehicle test benches. To achieve this, the methodology is divided into four distinct parts: acquiring real-world driving data, generating efficiency maps, validating the efficiency maps, and simulating and comparing the losses.

2.1 Measurement of Vehicle Data

To generate representative real-world driving data, a vehicle is equipped with measurement technology to record variables that affect friction losses, including wheel speed, ambient and bearing temperature. The static wheel loads, which influence the friction losses, are measured with wheel load scales [3, 4]. Figure 2 illustrates the measuring points using the example of the rear left wheel. The data is collected in urban, rural and highway environments in order to analyze diverse driving domains for identical driven bearings on the left side of an all-wheel-drive vehicle’s front and rear axle.

Fig. 2.
figure 2

Overview of the measuring positions of the test vehicle for the rear left wheel bearing.

2.2 Determination of the Efficiency Maps

The friction losses of the bearings are determined by means of measurements conducted on the friction torque test bench. A measurement cycle developed at the Institute of Automotive Engineering is employed to ascertain the losses occurring at the relevant operating points in accordance with the velocity and temperature for the front and rear left bearing of the test vehicle at different levels of radial wheel loads. The cycle effectively identifies the necessary operating points, thereby minimizing the time required for measurements. Figure 3 illustrates the efficiency maps for both bearings, which are dependent on the different applied radial wheel load levels.

Fig. 3.
figure 3

Determined efficiency maps for the front left bearing a) and rear left bearing b) as a function of velocity, temperature, and radial wheel loads.

The analysis indicates that the bearings experience their most significant friction losses under conditions of low temperatures and high velocities. This is primarily due to the increased viscosity of the lubricant, which hinders the formation of a lubricating film and leads to increased friction losses, particularly at high rotational speeds. Furthermore, the material behavior at lower temperatures and the consistency of the lubricant affect the bearing rolling element’s mobility, contributing to higher losses [5, 6]. The front left bearing (Fig. 3a) also exhibits higher friction losses in comparison to the rear left bearing (Fig. 3b). This can be attributed to the higher applied radial loads during the measurements, which are a consequence of the differing levels of wheel loads of the vehicle. To illustrate the influence of the radial load, Table 1 presents the maximum friction losses at the operating point at 20 ℃ and 140 km/h, as well as the arithmetic average losses over the total efficiency maps for both bearings.

Table 1. Maximum friction losses at the operating point at 20 ℃ and 140 km/h and the arithmetic average friction losses for the total efficiency map of the front and rear left bearing.

The increased radial load intensifies the pressure on the contact surfaces between the rolling elements and the raceway. Furthermore, elevated loads induce elastic deformation, which alters the shape of the contact surfaces and reduces the thickness of the lubricating film. This results in an average increase in friction losses, as observed in the efficiency map of the front left bearing, which can be up to 20% depending on the lubrication, bearing geometry and sealing type [5, 6].

2.3 Validation of the Efficiency Maps

Additional measurements are performed on the friction torque test bench to verify the accuracy of the efficiency maps. During this process, the losses determined from the test bench are compared with the simulated losses. The velocity profile used for validation is based on two WLTC cycles and the measured bearing temperature, as shown in Fig. 4a. Figure 4b compares the losses measured on the test bench with those calculated for the front left bearing. Additionally, it illustrates the cumulative deviation of the friction energy between the measurement and the simulation.

Fig. 4.
figure 4

Validation of the efficiency map depending on velocity and bearing temperature a) for the front left bearing with measurement on the test bench and simulating friction losses b).

The quantitative results of the friction losses determined using the efficiency map are in good agreement with the values measured on the test bench. However, a correlation analysis revealed an increasing qualitative discrepancy in losses, particularly at lower temperatures and velocities. This discrepancy arises because fewer operating points are available for modeling the efficiency maps at lower temperatures compared to higher temperatures. One reason for the reduced availability is that the bearings heat up rapidly during the efficiency map measurements at lower temperatures due to friction. Overall, the average friction losses per revolution for the complete cycle differ by 1.64%, and the cumulative deviation of the friction energy is 1.74 Wh.

2.4 Determination of the Friction Torque and Comparison

In the final step, the friction losses are simulated based on real-world driving operation data bearing temperatures and velocities, which were determined in Sect. 2.1 by using the test vehicle for urban, rural, and highway driving domains, to assess their contribution to drivetrain losses. Furthermore, the losses are calculated based on data recorded on a homologation-relevant vehicle dynamometer to illustrate differences between measurements on the dynamometer and real-world driving conditions. Figure 5a displays the velocity profile for real-world driving operation and dynamometer testing, bearing and wheel housing temperatures for the front left bearing for the rural driving domain. Figure 5b illustrates the friction losses simulated with the help of the recorded measurement data and using the efficiency map, to compare the conditions for real-world driving operations and dynamometer testing.

Fig. 5.
figure 5

Comparison of friction losses for the front left bearing b) for rural driving domain calculated with the efficiency map for real-world driving conditions and dynamometer testing a).

The temperature difference in the wheel housing between the data for real-world driving conditions and dynamometer testing is significant, mainly attributable to reduced airflow through the dynamometer’s air blower. This notably affects the heat convection of the bearings to the environment, especially at higher velocities. In this instance, a growing disparity in bearing temperature is evident from a time of 500 s due to this phenomenon. Consequently, the bearing experiences a greater temperature increase on the dynamometer, resulting in a reduction of friction losses. This results in a cumulative deviation of the friction energy over the rural cycle of 8.18 Wh. Figure 6 presents the average friction losses per revolution for all driving domains and both bearings in comparison between real-world driving and dynamometer conditions. The overview indicates that the front left bearing consistently experiences elevated friction losses across various driving domains, which is approximately 20% higher than for the rear left bearing. This is primarily attributed to the increased wheel load.

Fig. 6.
figure 6

Comparison of the average friction losses per revolution for the front and rear left wheel bearing between real-world driving operations and dynamometer testing data.

Furthermore, the varying friction losses resulting from declining average velocities across highway, rural, and urban driving domains are discernible. Additionally, discrepancies between real-world driving conditions and dynamometer testing data results are evident. In particular, real-world conditions indicates losses up to 12% higher due to improved heat dissipation from the airflow compared to the dynamometer.

3 Conclusion

The results presented in this study demonstrate the friction losses associated with the wheel bearings in the drivetrain across various driving domains and influencing parameters. They also illustrate the discrepancies between real-world driving operations and dynamometer testing due to varying temperature conditions, which can present challenges in conducting real driving emissions cycle measurements. Furthermore, analyzing the differences in wheel loads between real-world driving operations and dynamometer testing in the future would be beneficial for further investigating these variances. This approach can be applied to other components, allowing for the evaluation of component behavior in real-world vehicle operations.