Electric Vehicle Li-ion Battery Evaluation based on Internal Resistance Analysis David Anseán, Manuela González, Juan Carlos Viera, Juan Carlos Álvarez, Cecilio Blanco Electrical Engineering Department University of Oviedo Gijón, Spain
[email protected] Abstract—Internal resistance (IR) is considered one of the most important parameters of a battery, as it is used to evaluate the battery’s power performance, energy efficiency, aging mechanisms or equivalent circuit modeling. In addition, in electric vehicle (EV) applications, the IR provides essential information related with regenerative braking capabilities, dynamic charge and discharge efficiencies, or physical degradation of the battery. This work aims to provide the insight details of the IR of a battery under several testing conditions and methods, to present its practical implications on EVs. The experimental tests are carried out on lithium iron phosphate (LFP) batteries ranging from 16 Ah to 100 Ah, suitable for its use in EVs. We study the IR dependency with battery’s capacity, SOC and the charge/discharge rate; also, the convenience of using a certain IR measurement method is evaluated. Furthermore, the main results are put into context for practical EV applications, to enhance the design of battery management systems (BMS) in relation with the system’s energy efficiency. Keywords—Internal resistance; Internal resistance measurement method; Electric Vehicle Battery ; Lithium iron phosphate batteries
I.
INTRODUCTION
Some of the most important features and specifications of EVs are determined by its battery system. Automotive manufacturers seek for batteries with optimum characteristics: high energy and power densities, inherent safety, optimal thermal performance, and low cost. Similarly, the battery system conditions the EVs range and acceleration. The range can be increased by adding more capacity to the battery system using higher energy density cells, whereas acceleration can be also increased by selecting batteries with higher power density cells. Therefore, both energy and power density play a significant role when choosing the battery for an EV. In order to characterize the performance of a battery system for an EV, the IR has to be evaluated. The IR is a key parameter of a battery: it is directly linked to its power performance, energy efficiency, ability to perform fast charging and regenerative braking, and is also related to physical cell degradation [1,2]. All this set of parameters are crucial for the correct functioning of the EV and its battery management system (BMS). The IR of a battery is a complex, non-linear system which shows capacitive, resistive and inductive behavior interrelated
Víctor Manuel García Physical and Analytical Chemistry Department University of Oviedo Gijón, Spain among them [3]. In addition, the IR is also dependent on its constructive materials, geometry, and physical and electrochemical phenomena [4-6]. As a consequence, the IR of a battery changes with the charge/discharge current rates, state of charge (SOC), state of health (SOH) and temperature. Similarly, battery aging mechanisms are also related with the IR: in essence, the IR increases with battery aging [2,7]. In order to analyze the IR of a battery, various methods have been proposed: DC pulse current [6,8,9], voltage curve difference [10-12], or the method proposed by the U.S. Department of Energy [13,14], which have been widely adopted by battery manufacturers [8]. These methods share the advantages of easiness to implement, simple calculations and they provide realistic results, which are all main factors for its applicability on BMSs. However, it is important to mention that the IR of a battery may differ upon the IR method used; therefore, a proper analysis must be carried out [3,6,9]. In this work, we present the IR results obtained from four fresh lithium iron phosphate (LFP) batteries under numerous testing conditions. The primary aim is to investigate the IR dependency of the four batteries at different SOC ranges and charge/discharge currents, by using three different IR methods. The results are useful to evaluate and discuss the importance of the IR and its dependencies, the advantages and drawbacks of the IR methods used, and its implications for EV applications. II.
INTERNAL RESISTANCE DESCRIPTION
The internal resistance of a battery is defined as the opposition or resistance to the flow of an electric current within a battery. When the battery is connected to a load and the current passes through the closed circuit, the voltage across the battery decreases (see Eq. 1) due to several sources of polarization [4,6]: .
(Eq. 1)
where U is the voltage of the battery under load and UOCV is the open circuit voltage (OCV) which represents the thermodynamics of the battery [4]. The polarization losses represented by are associated both from the ionic resistance of the electrolyte and the electronic resistance of the terminals and contacts in the electrodes, and are governed by the Ohm’s law. The charge transfer or activation polarization is the energy associated with chemical reactions which . is the diffusion polarization, occur on the electrodes, and
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which occurs due to mass transport liimitations in the electrolyte and electrode materials [4,6,15]. Both the charge transfer and diffusion polarizations are governed by the generalized Butler–Volmer equation [4]. The dynamic behavior of a battery in relation with the polarization losses is shown in Fig. 1. The time domain of a battery is in a wide range, from microsecondds up to hours [15], and each polarization source is time relatedd with the voltage evolution. The sums of all the polarization losses, which are directly related with the total IR of the batteery, are influenced by both internal and external factors. This T includes the battery’s SOC, SOH and design parameters, such as chemistry materials, electrolytes or additives [4,6,9,15]. Most influential external parameters are the temperature, cuurrent rate and the history of the battery [9,15]. To summarize, the IR of a battery is a non-linear n complex system dependent on several parameters, both internal and external. Therefore, an accurate evaluation off the IR has to take into account the aforementioned battery charaacteristics.
Cell 1
Cell 2
Cell 3
Cell 4
Nominal capacity
16 Ah
42 Ah
60 Ah
100 Ah
Max. continuous discharge
160 A (10 C) 80 A (5 C) 500 g Cylindrical
126 A (3 C) 84 A (2 C) 1000 g Pouch
180 A (3 C) 180 A (3 C) 2000 g Prismatic
300 A (3 C) 300 A (3 C) 3200 g Prismatic
