Comparative Analysis of Lithium-Ion Battery Resistance Estimation Techniques for Battery Management Systems

Abstract

Safe and efficient operation of a battery pack requires a battery management system (BMS) that can accurately predict the pack state-of-heath (SOH). Although there is no universal definition for battery SOH, it is often defined based on the increase in the battery's internal resistance. Techniques such as extended Kalman filter (EKF) and recursive least squares (RLS) are two frequently used approaches for online estimation of this resistance. These two methods can, however, be computationally expensive, especially in the case of a battery pack composed of hundreds of cells. In addition, both methods require a battery model as well as chemistry specific parameters. Therefore, this paper investigates the performance of a direct resistance estimation (DRE) technique that requires minimal computational resources and can be implemented without any training data. This approach estimates the ohmic resistance only when the battery experiences sharp pulses in current. Comparison of results from the three algorithms shows that the DRE algorithm can accurately identify a degraded cell under various operating conditions while significantly reducing the required computational complexity. The findings will further advance diagnostic techniques for the identification of a weak cell in a large battery pack.

Open and Flexible Li-ion Battery Tester Based on Python Language and Raspberry Pi

“…The mean values of the readings coming from the two instruments I CSTi and I REFi for each i-th step were evaluated and compared. The current absolute error E Ii is the difference between the two values expressed by equation (4), whereas the linear regression function is described in (5), where Off I and G I are the offset and gain parameters of the function. Figure 12b shows the linear regression fit of the E Ii points.…”

“…Therefore, the SoH can be defined using either one of these two metrics. In the first case, the actual deliverable capacity of the cell is compared to the value when the battery is fresh, whereas the actual internal resistance is compared to its nominal one in the second case [5]. However, in a fully electric vehicle, such as an E-scooter, the capacity is the most interesting parameter, since it determines the operating range of the vehicle [5].…”

“…In the first case, the actual deliverable capacity of the cell is compared to the value when the battery is fresh, whereas the actual internal resistance is compared to its nominal one in the second case [5]. However, in a fully electric vehicle, such as an E-scooter, the capacity is the most interesting parameter, since it determines the operating range of the vehicle [5]. As indicated in [6], LIBs used in electric traction applications are considered at end of their life when they have lost 20% of the nominal capacity, i.e., when SoH reaches 80%.…”

Carbon Footprint and Water Footprint of Electric Vehicles and Batteries Charging in View of Various Sources of Power Supply in the Czech Republic

“…According to the ACEA, 76% of all electric vehicle (EV) charging points in the EU are located in just four countries. Out of 100,000 charging points across the EU today, almost 30% are located in the Netherlands (32,875), 22% in Germany (25,241), 14% in France (16,311), and 12% in the United Kingdom (14,256). A total of 684 charging points are available in the CR.…”

“…Refs. [16,17] assessed Lithium-ion batteries as for their resistance and aging. [18] focused on costs ownership analysis of electric vehicles in comparison with internal combustion engine vehicles.…”