Advantech Europe

Outdated battery measurement solutions can impact e-mobility vehicle performance

Author : Andrew Herrera, Keysight Technologies

08 December 2023

Figure 1: An advanced battery measurement solution with software that creates a dynamic discharge current data collection
Figure 1: An advanced battery measurement solution with software that creates a dynamic discharge current data collection

To fully maximise the potential of low-power e-mobility vehicles, it is crucial to understand these vehicles' battery performance and characteristics. Specifically, you need to understand the battery charge discharge characteristics, battery performance due to various load conditions and electronics used in the system, and, more importantly, aging battery performance.

In recent years, low-power e-mobility vehicles have become extremely popular as sustainable and efficient modes of transportation. Electric bicycles and scooters offer numerous benefits, including reduced carbon emissions and lower operating costs. 

Key factors impacting battery life

In general, load affects the power and travel distance of e-mobility vehicles. Load refers to the combined weight of the vehicle's rider, cargo, and accessories. As the load increases, the power requirements of the electric motor also increase, leading to a decrease in the travel distance. Similarly, adding more high-end features such as a touchscreen user interface, wireless connection feature, GPS for navigation, headlights, or a high-performance brushless DC motor will consume more power from the battery. It is a constant battle between customers' requested features versus battery performance, requiring manufacturers to make an informed decision to add or remove certain features, without further sacrificing battery performance and customer demands.

For engineers navigating the intricate landscape of e-mobility, comprehending the complex challenges involved in measuring and optimising battery performance in electric vehicles (EVs) is crucial. These challenges serve as a litmus test for the resilience and efficiency of energy storage systems within EVs. To gauge battery health, engineers must grapple with several intricate factors, including battery chemistry, depth of discharge, charge rates, and temperature management. However, translating these metrics into real-world scenarios presents hurdles, as the dynamic nature of driving patterns and the influence of vehicle weight can be challenging to quantify precisely.

In this ever-evolving field, engineers must understand the complexities of battery performance, and innovate and adapt to these challenges. Navigating this terrain with the right expertise is essential to designing resilient, efficient, and high-performance battery systems for the future of e-mobility.

Figure 2: Example of advanced emulation and test software running an emulation operation mode setting and the completed test result
Figure 2: Example of advanced emulation and test software running an emulation operation mode setting and the completed test result

Understanding battery aging and its implications

Further, the performance of an EV with an aging battery is crucial. An aged battery is a battery that has deteriorated over time and no longer performs at its optimal capacity. Rechargeable batteries such as Lithium-ion (Li-ion) batteries have a limited lifespan and will gradually lose their ability to hold and deliver a charge as they chemically age. However, Li-ion batteries tend to have a finite charge/discharge cycle; their capacity starts to degrade once they meet their limit, further reducing the travel distance of the EV.

Many factors affect the battery power and performance of e-mobility vehicles, which are critical for engineers to understand before they can unlock their full potential as a sustainable and efficient mode of transportation. An advanced battery test solution that offers various test capabilities, such as battery cycler test, emulation test, charge/discharge test, and profiler test, can help to unleash the potential of low-power e-mobility products.

Measuring battery performance

When measuring battery performance, engineers must get precise and accurate measurements to ensure that they take full advantage of battery capacity and provide all e-mobility vehicle features. Battery measurement solutions must provide advanced results and allow engineers to use features such as profiling and data operation modes to create battery discharge models. Discharge modelling provides critical data results, such as performance prediction, efficiency optimisation, and battery health management.

One of the advantages of using advanced battery measurement solutions and software is creating a battery charge or discharge model from the physical battery with profiler operation modes. A battery charge or discharge model enables engineers to analyse the battery's performance, including capacity, internal resistance, voltage, and current at various temperatures and operational conditions. The software automatically generates a reusable battery model for the battery emulation test. Engineers can create a battery discharge model by constantly or dynamically discharging the battery by providing the advanced software's current, power, or resistance information. Figure 1 shows an example of pairing an advanced battery measurement solution with software to create a dynamic discharge current data collection.

Andrew Herrera, Product Marketing Manager for RF test software at Keysight Technologies
Andrew Herrera, Product Marketing Manager for RF test software at Keysight Technologies

Other advanced features that measure battery performance for low-power e-mobility vehicles are battery emulation operation modes. These modes enable engineers to understand how a targeted device under test (DUT) would behave when connected to a battery with unique characteristics, without needing a physical battery. The advanced features provide a safer test environment, while saving engineers time by eliminating the need to charge the physical battery after every test. In addition, with emulation operation modes, engineers can accurately and seamlessly run the test on the DUT at a specific battery state of charge (SoC), simply by entering the desired battery SoC in the software.

To run a battery emulation test using advanced battery test and emulation software, engineers need to use a battery model extracted from the physical battery. The battery model contains information such as capacity, cut-off voltage, internal resistance, and voltage tied to the battery SoC. This type of software includes predefined battery models that engineers can use directly in the test.

After loading the selected battery model, the software automatically displays all the battery information. Figure 2 shows the setting used in an example battery emulation test at 98.1 percent SoC. However, engineers can further modify the settings, such as battery capacity rating, current limit, or initial SoC, that suit the test and application requirements. Maintaining precise control over the battery's SoC is paramount in e-mobility battery safety testing. The vehicle's battery management system (BMS) must undergo comprehensive testing to ensure its readiness to handle battery over-discharge or overcharging scenarios. In such situations, the BMS must be capable of promptly halting the charging or discharging operation to safeguard the battery.

Suppose engineers opt to employ a cell battery model for this test. In that case, those using advanced battery emulation and test software can activate battery pack features. This capability allows engineers to configure the number of series and parallel connections of the battery cells, effectively simulating a battery pack to achieve higher voltage and current outputs. Additionally, users can set the cut-off condition of the test by defining the target SoC or terminal voltage. Adding overvoltage protection increases safety measures.

Figure 3: An advanced emulation and test software running cycler operation mode settings with the completed test result
Figure 3: An advanced emulation and test software running cycler operation mode settings with the completed test result

Finally, engineers must analyse battery charging and discharging to ensure that a battery performs at its peak capabilities in an e-mobility vehicle; it can affect performance over time. However, with charging and discharging, an engineer must also look at battery aging, which can harm vehicle range, charging frequency, and performance degradation. Features such as cycler operation modes in battery measurement solutions enable engineers to create a custom sequence of charging, resting, and discharging a battery up to 1,000 cycles of operations to measure battery performance and capacity degradation over time quantitatively. Figure 3 shows an example test using an advanced battery test and emulation software.

The test shows a new cycle sequence consisting of a constant 10A current discharge – rest, charge, and rest operation – with 10 repetitive cycles. The cycle sequence accelerates the aging battery test for a quick feature demonstration. For the actual battery aging test, engineers can further discharge the battery to a much lower voltage, add more charge/discharge/rest sequences per cycle, increase the number of cycles, and use the dynamic discharge current data for more accurate results. Users can also define the cut-off condition to automatically stop the cycler operation mode when capacity loss reaches a certain percentage.

Conclusion

Regarding e-mobility vehicles, accurate battery performance measurements are critical to ensure that the battery in the low-power vehicle performs as expected. Engineers using advanced battery solutions and software that provide the correct data will better understand battery performance. Errors in the data can negatively impact battery performance and minimise a battery's potential. Since e-mobility vehicles have a lot of electronic components and features, engineers need to ensure that the batteries in them deliver their best potential. An incorrect battery measurement solution can significantly impact the performance of e-mobility vehicles.


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