In the rapidly evolving field of new energy vehicles, the electromagnetic compatibility (EMC) performance of EV power battery systems is critical for ensuring reliable operation. As a key component, the China EV battery system must function under various electromagnetic environments without causing interference or being susceptible to it. This study focuses on evaluating the radiated emissions of EV power battery systems under different testing configurations, emphasizing the impact of auxiliary devices and layout factors. We explore how variations in load simulation—using resistive loads, electronic loads, and excitation devices—affect EMC outcomes, particularly in relation to cable distances, antenna positioning, and grounding methods. The goal is to optimize testing consistency and reduce development costs for China EV battery applications.
The importance of EMC in EV power battery systems cannot be overstated, as these systems supply high-voltage power to motors and control units, making them potential sources of electromagnetic interference (EMI). In testing, simulating real-world conditions is challenging due to the lack of standardized auxiliary devices across laboratories. This leads to discrepancies in results, complicating compliance and design improvements for China EV battery technologies. Our approach addresses this by systematically analyzing key factors influencing radiated emissions, providing insights that enhance test repeatability and support the advancement of robust EV power battery designs.
To conduct this analysis, we adopted a method based on standardized EMC testing protocols, specifically referencing guidelines for high-voltage components. The radiated emission tests were performed in a 1-meter anechoic chamber, ensuring a controlled environment. The setup included high-voltage and low-voltage cables with a total length of 1700 mm, with 1500 mm parallel to the ground plane front edge, all placed on non-conductive, low-dielectric constant material (ε_r ≤ 1.4). Key parameters, such as cable separation, antenna height, and grounding, were varied to assess their effects on emissions from the China EV battery system.
Three types of auxiliary devices were employed to simulate the load conditions of an EV power battery in real vehicles. First, a pure resistive load with a power rating of 4 kW, capable of handling currents from 0 to 50 A and voltages from 0 to 450 V, was used to represent basic resistive characteristics. Second, an electronic load with a power rating of 30 kW, supporting currents of 0–120 A and voltages of 24–750 V, served as a bipolar power source that could discharge or supply power, mimicking dynamic operational scenarios. Third, an excitation device, developed in-house as a large capacitive load, simulated the motor load typically found in vehicles, providing a more realistic representation of EV power battery behavior. These devices were selected to cover a range of common testing scenarios for China EV battery systems, enabling a comprehensive evaluation of EMC performance.
The factors investigated in this study were chosen based on industry experience and their potential impact on radiated emissions. These include the relative distance between high-voltage and low-voltage cables (Factor A), the height of the receiving antenna above the ground (Factor B), the distance from the receiving antenna to the reference center point (Factor C), and the grounding position relative to the battery management system (Factor D). For Factor A, distances of 0 mm, 100 mm, and 200 mm were tested, as closer proximity can increase parasitic parameters and coupling interference. Factor B involved antenna heights of 900 mm, 1000 mm, and 1100 mm, accounting for typical measurement variations. Factor C considered distances of 900 mm, 1000 mm, and 1100 mm from the reference point, reflecting possible deviations in setup. Factor D evaluated grounding positions labeled as “close to main control,” “far from main control,” and “moderate from main control,” influencing the return path of interference signals in the EV power battery system.
An orthogonal experimental design was utilized to efficiently analyze these four factors at three levels each, reducing the number of tests while maintaining statistical robustness. The orthogonal array comprised nine test combinations, as summarized in the table below, which outlines the specific levels for each factor in the context of China EV battery testing.
| Test No. | Factor A: Cable Distance (mm) | Factor B: Antenna Height (mm) | Factor C: Antenna to Reference (mm) | Factor D: Grounding Position |
|---|---|---|---|---|
| 1 | 0 | 900 | 900 | Close to Main Control |
| 2 | 0 | 1000 | 1100 | Far from Main Control |
| 3 | 0 | 1100 | 1000 | Moderate from Main Control |
| 4 | 100 | 900 | 1100 | Moderate from Main Control |
| 5 | 100 | 1000 | 1000 | Close to Main Control |
| 6 | 100 | 1100 | 900 | Far from Main Control |
| 7 | 200 | 900 | 1000 | Far from Main Control |
| 8 | 200 | 1000 | 900 | Moderate from Main Control |
| 9 | 200 | 1100 | 1100 | Close to Main Control |
Prior to testing, the anechoic chamber’s background noise was verified to ensure it met requirements, with both horizontal and vertical polarization data showing no significant interference sources. This step was crucial for obtaining accurate radiated emission measurements for the China EV battery system. Each of the nine test combinations was evaluated over the frequency range of 30 MHz to 1000 MHz, divided into 13 sub-bands. The maximum emission level in each sub-band was recorded, and the sum of these maxima was used as the overall emission indicator for statistical analysis. This approach allowed us to quantify the impact of each factor on the EV power battery’s EMC performance.
The data collected from these tests were processed using range analysis to determine the optimal conditions and the relative influence of each factor. For instance, the mean value \( k \) and range \( R \) were calculated for each factor level. The formula for the mean value \( k_i \) of a factor at level \( i \) is given by:
$$ k_i = \frac{K_i}{n} $$
where \( K_i \) is the sum of emission values for that level across all tests, and \( n \) is the number of tests at that level. The range \( R \) is then computed as:
$$ R = \max(k_i) – \min(k_i) $$
This calculation helps identify which factor has the greatest effect on radiated emissions in the China EV battery system. Below, we present the summarized data for each auxiliary device, starting with the resistive load.
| Test No. | Sum of 13 Sub-band Emissions |
|---|---|
| 1 | 39.967 |
| 2 | 40.637 |
| 3 | 34.082 |
| 4 | 76.783 |
| 5 | 76.421 |
| 6 | 63.025 |
| 7 | 62.509 |
| 8 | 58.804 |
| 9 | 54.084 |
For the resistive load, the \( K \) values for each factor were calculated as follows: For Factor A (cable distance), \( K_1 = 39.967 + 40.637 + 34.082 = 114.686 \), \( K_2 = 76.783 + 76.421 + 63.025 = 216.229 \), and \( K_3 = 62.509 + 58.804 + 54.084 = 175.397 \). The corresponding mean values are \( k_1 = 38.228 \), \( k_2 = 72.076 \), and \( k_3 = 58.465 \), resulting in a range \( R = 33.847 \). Similarly, for Factors B, C, and D, the calculations yield the following results, demonstrating the influence on the EV power battery emissions.
| Factor | k1 | k2 | k3 | Range R |
|---|---|---|---|---|
| A: Cable Distance | 38.228 | 72.076 | 58.465 | 33.847 |
| B: Antenna Height | 59.753 | 58.620 | 50.397 | 9.356 |
| C: Antenna to Reference | 53.932 | 57.670 | 57.168 | 3.738 |
| D: Grounding Position | 56.824 | 55.390 | 56.556 | 1.434 |
From this analysis, the optimal test condition for the resistive load is A2B1C2D1, meaning a cable distance of 100 mm, antenna height of 900 mm, antenna to reference distance of 1000 mm, and grounding close to the main control. This combination produces the highest radiated emissions, indicating a worst-case scenario for EMC evaluation of the China EV battery. The range values show that Factor A (cable distance) has the most significant impact, followed by Factor B (antenna height), Factor C (antenna to reference distance), and Factor D (grounding position). This hierarchy underscores the critical role of cable layout in managing emissions for EV power battery systems.
Moving to the electronic load, the emission data were processed similarly, as shown in the table below. The sums of sub-band emissions for each test are provided, enabling a comparative analysis with other auxiliary devices.
| Test No. | Sum of 13 Sub-band Emissions |
|---|---|
| 1 | 34.201 |
| 2 | 35.842 |
| 3 | 42.397 |
| 4 | 65.774 |
| 5 | 64.581 |
| 6 | 45.616 |
| 7 | 73.418 |
| 8 | 62.639 |
| 9 | 64.856 |
The range analysis for the electronic load reveals the following mean values and ranges. For Factor A, \( k_1 = 37.480 \), \( k_2 = 61.205 \), \( k_3 = 66.971 \), and \( R = 29.491 \). For other factors, the calculations are summarized in the table, highlighting the effects on the China EV battery system.
| Factor | k1 | k2 | k3 | Range R |
|---|---|---|---|---|
| A: Cable Distance | 37.480 | 61.205 | 66.971 | 29.491 |
| B: Antenna Height | 57.797 | 54.354 | 50.956 | 6.841 |
| C: Antenna to Reference | 47.485 | 60.132 | 55.490 | 12.647 |
| D: Grounding Position | 54.546 | 51.625 | 56.936 | 5.311 |
For the electronic load, the optimal test condition is A3B1C2D3, corresponding to a cable distance of 200 mm, antenna height of 900 mm, antenna to reference distance of 1000 mm, and grounding at a moderate position. This setup yields the highest emissions, emphasizing the importance of cable distance in EMC assessments for EV power battery systems. The range order is Factor A > Factor C > Factor B > Factor D, indicating that cable distance and antenna positioning are more influential than grounding for this auxiliary device. Such findings are vital for standardizing tests on China EV battery technologies.
Finally, for the excitation device, the emission data are presented in the table below. This device simulates motor loads, providing a realistic scenario for evaluating the China EV battery in dynamic conditions.
| Test No. | Sum of 13 Sub-band Emissions |
|---|---|
| 1 | 42.946 |
| 2 | 38.266 |
| 3 | 43.837 |
| 4 | 49.089 |
| 5 | 60.154 |
| 6 | 59.987 |
| 7 | 63.605 |
| 8 | 54.899 |
| 9 | 56.648 |
The range analysis for the excitation device shows: For Factor A, \( k_1 = 41.683 \), \( k_2 = 61.248 \), \( k_3 = 58.384 \), and \( R = 19.565 \). The complete results are tabulated, illustrating the impact on EV power battery emissions.
| Factor | k1 | k2 | k3 | Range R |
|---|---|---|---|---|
| A: Cable Distance | 41.683 | 61.248 | 58.384 | 19.565 |
| B: Antenna Height | 51.880 | 51.106 | 53.490 | 2.384 |
| C: Antenna to Reference | 52.610 | 55.865 | 48.001 | 7.864 |
| D: Grounding Position | 53.249 | 53.952 | 49.275 | 4.677 |
For the excitation device, the optimal condition is A2B3C2D2, with a cable distance of 100 mm, antenna height of 1100 mm, antenna to reference distance of 1000 mm, and grounding far from the main control. This results in the highest emissions, further confirming the dominance of cable distance in affecting EMC performance for China EV battery systems. The range order is Factor A > Factor C > Factor D > Factor B, suggesting that cable distance and antenna-to-reference distance are key, while antenna height has minimal impact. This insight aids in focusing efforts on critical parameters during EV power battery development.
In conclusion, this study demonstrates that the relative distance between high-voltage and low-voltage cables is the most influential factor on radiated emissions across all auxiliary devices—resistive load, electronic load, and excitation device—used in testing China EV battery systems. The optimal test conditions identified provide a framework for achieving maximum emission levels, which can help in assessing and mitigating EMC risks early in the design phase. For the EV power battery industry, adopting these findings can lead to more consistent testing outcomes, reduced troubleshooting time, and enhanced reliability. Future work could explore additional factors or integrate advanced simulation models to further optimize EMC performance for evolving China EV battery applications.
Overall, the emphasis on cable management in EMC testing underscores its critical role in ensuring the electromagnetic integrity of EV power battery systems. As the demand for electric vehicles grows, such research contributes to the development of safer and more efficient China EV battery technologies, supporting global sustainability goals. By leveraging orthogonal experimental designs and statistical analysis, we have provided actionable insights that can be applied in laboratories and manufacturing settings to improve the EMC robustness of these essential components.