Multiple Cell Lithium-Ion Battery System Electric Fault Online Diagnostics Bing Xia, and Chris Mi
Zheng Chen
Brian Robert
University of Michigan Dearborn Dearborn, Michigan, 48128
[email protected],
[email protected]
Kunming University of Science and Technology Kunming, China, 650500
[email protected]
Ford Motor Company Dearborn, Michigan, 48121
[email protected]
Abstract-This paper introduces an integrated online electrical safety diagnostic algorithm for lithium-ion battery systems, which includes the detection of over charge, over discharge, external short circuit and internal short circuit faults. Experiments were conducted for each fault and the safety criteria, presented by a combination of voltage, current and temperature, were built according to empirical results. Based on the criteria, an integrated electrical fault diagnostic algorithm is proposed. Experimental results show that the proposed algorithm is effective and robust at detecting and distinguishing electric faults for multiple cell battery arrangements online.
Keywords-over charge; over discharge; internal short circuit; external short circuit; fault diagnostic. 1.
INTRODUCTION
The booming development of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) has created a large demand for reliable energy storage systems [1]. Lithium-ion batteries are highly competitive among all kinds of alternatives, due to their high energy density, high power density, low self discharging and no memory effect [2, 3]. As more and more lithium-ion batteries are being utilized in the energy storage systems of EVs and PHEVs, it becomes important to manage the batteries to ensure their safe operation [4]. Hence, there is an increased interest in monitoring battery status. There is a multitude of research on the estimation of battery state-of charge (SoC) [5], state-of-health (SoH) [6], and remaining useful life (RUL). Furthermore, battery fault diagnosis and prognostics is an emerging field that deals with electrical, mechanical and thermal faults. Among these, electrical faults are of keen interest and require immediate identification. Abundant research has been conducted to investigate the electric faults of lithium-ion battery cells [7, 8]. In [9], the behavior of lithium-ion batteries experiencing over charging conditions is studied, and the rate of charge is found to be a key factor that results in cell ruptures. In [10], current collector corrosion enhanced by over discharging, which accelerates the aging process, is studied. Abusive heat modeling is used to estimate kinetic parameters and to guide designs for batteries that are more tolerant to thermal runaway in [11, 12]. Internal short circuit (ISC) faults are modeled, simulated and validated in [13] with nail penetration, indentation and pinch tests. The risk of thermal runaway under ISC is also analyzed in [14, 15]. An external short circuit (ESC) is an important electric fault due to the potential severity of the extremely high current involved, which is can be greater than 10 C, where C stands for the
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multiple of current with respect to the capacity of the cell in Ah [16, 17]. To summarize, most of the previous work in battery safety focuses on the mechanisms and diagnostics for individual electric faults; however, this is not adequate to ensure safe operation in a battery pack system, where the safety diagnostic algorithm should tackle combined electric faults for a system instead of for individual cells [18]. The algorithm not only requires the development of safety threshold values, but also needs to determine the distinction among electric faults to ensure proper hazard mitigation [19, 20]. In order to build an integrated battery system electric diagnostic algorithm, experiments were conducted in which the voltage, current and temperature responses of cells in normal operation were compared to those in each of the electric faults, including over charge, over discharge, ESC and ISC. For these results, threshold values for each electrical fault were obtained through thermal and electric modeling of a series string. Based on these threshold values, an integrated system level safety diagnostic algorithm is proposed and tested online with a connected cell array. Experimental results show the feasibility of the proposed algorithm. II.
EXPERIMENTS FOR ELECTRIC FAULTS
In order to identify battery electrical faults, experiments are conducted beyond normal operating conditions, including: ESC, ISC, over charge and over discharge. Meanwhile, the voltage, current and battery surface temperature are recorded to build the diagnosis algorithm. In this paper, 18650 lithium-ion phosphate cells are selected to carry out the mentioned experiments. The detailed cell information is listed in Table 1. The nominal capacity of the cell is 1.40 Ah and the normal voltage operation range is 2.0 V to 3.65 V. The maximum pulse discharge current is 7 A. A. Definition of electric faults The definition of electric faults may vary depending on applications. In this paper, the four types of electric faults are defined as follows: 1) External short circuit: The battery is discharging at a current that is higher than the maximum discharge current, the terminal voltage is close to zero and the temperature is increasing quickly. 2) Internal short circuit: The battery is physically damaged due to penatration of a sharp object.
3) Over charge: The battery is charged above its maximum voltage limit. 4) Over discharge: The battery is discharged below its minimum voltage limit.
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From the observation on the over charge experiment, the voltage and temperature are key parameters in over charge detection. C.
Over discharge experiments
In order to conduct over discharge experiments, all six cells connected in series are charged to 100% Soc. The discharge is stopped when the lowest voltage value among all the cells reaches 1.5 V, which is lower than the lower limit of the normal operation range. The voltage and temperature responses are shown in Fig. 3 and Fig. 4, respectively. D. ESC experiments To characterize the occurrence of ESC faults, single cell level ESC tests are conducted for lOs with 100% initial Soc. The external resistance for the short circuit is 17 mn. The detailed steps and equipment to perform the experiment are introduced in [17]. The experiment is repeated four times and the voltage, current and temperature responses are shown in Figs. 4-6, respectively. The current first rises to around 60 A, then decreases slowly until the ESC fault terminates. The temperature reaches a maximum value of 45°C after the battery is shorted for 60s, as shown in Fig. 7. The voltage drops to almost zero instantly and recovers to the nominal range after terminating the fault. Obviously, current and voltage react faster than temperature.
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Fig. 1: Voltage responses for the over charge experiment.
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B. Over charge experiments Over charge tests are performed in a six-cell series configuration (lP6S). The string of cells is charged at 1C rate with a constant current charging scheme. The initial SoC of all the cells is 0%. During the experiment, the maximum terminal voltage among all six of the cells is used to control charging, i.e., the charging will be terminated when the maximum terminal voltage of the cells reaches 4.65 V. Compared with the maximum charge voltage in Table I, this value is 1 V higher than the normal operation range of the cells, and the over charge fault is thus induced for the six cells, as shown in Fig. 1. The temperature responses in Fig. 2 show that the temperature increases more rapidly after 3100 s, which corresponds to the start point of the over charge fault in Fig. 2.
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When the battery cells are connected in series, the subject cell associates with two current loops as shown in Fig. 8. The
first loop is the current driven by the electronic load, and the second loop is formed by its own short circuit path. From the circuit analysis, when the ESC fault is induced, all the current tends to flow through the shorted path because of its much lower resistance. In this way, the battery cell is experiencing only the ESC current produced by itself. This current is the same as in the single cell ESC condition.
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voltage and temperature responses are logged, and shown in Fig. 10 and Fig. 11, respectively. When the depth is 5 mrn, the voltage drops and is then finally maintained at approximately 3.2 V. When the depth is 10 mrn and 15 mrn, the voltage drops to less than 0.5 V and the temperature increases to greater than 35°C.
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E. ISC experiments ISC experiments are performed at the single cell level with no load applied. A press drill of diameter 2 mrn is used to penetrate the battery cell. Cells with 100% initial SoC are tested with 5 mm, 10 mrn and 15 mm penetration depths from the center of the horizontally oriented cylindrical cell to induce an ISC, as shown in Fig. 9. This simulates the case where the cell is penetrated by a foreign conductive object. The terminal
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III.
SAFETY DIAGNOSTIC ALGORITHM DEVELOPMENT
Based on experimental results, a preliminary diagnostic algorithm is postulated according to aforementioned definitions of the electric faults, as shown in Fig. 12. The occurrence of electric faults is determined by comparing the battery status including voltage, current and temperature - with the predefined threshold values, VEse (dT/dt)Ese lEse Voe (d V/dt)lse (dT/dt)ISCI, (dT/dt)ISCh, and VOD, where VESC is the voltage lower limit to determine an ESC, (dT/dt)ESC is the temperature increase rate upper limit to determine an ESC, lEsc is the upper current limit to determine an ESC, (d V/dt)ISCI is the voltage decrease rate lower limit to determine an ISC, (d V/dt)JSCh is the voltage decrease rate upper limit to determine an ISC and (dTldt),sc is the temperature increase rate threshold value to determine an ISC.
detection is determined as twice the maximum temperature increase rate in normal operation. Thus, (dT/dtJEsc is 0.3 °C/s. The current threshold value for ESC detection is assigned according to Table I, i.e., lEsc is 7 A. The voltage threshold value is found from Fig. 5, where the highest voltage value among all the ESC experiments is 0.273 V, and twice this value is assigned for VEsc as a measurable margin.
A. Threshold value determination for over charge and over discharge The over charge and over discharge voltage threshold values can be determined based on their definitions, i.e., VOD is 3.65 V and VOD is 2.0 V according to Table I. In the algorithm, the temperature is not used even though changes in surface temperature are observed in the experiments. This is due to the fact that the temperature rises are not significant compared to ambient temperature changes and heat buildup from aggressive charge and discharge cycles.
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IV.
EXPERIMENTAL VERIFICATION
It is essential to verifY the proposed observation algorithm when the battery is in operation. Hence, a hardware-in-the-Ioop platform is constructed to simulate vehicle operation and demonstrate the algorithm under different drive cycles. The system includes a charge subsystem, a discharge subsystem, and a data acquisition system. All the subsystems are connected with a data acquisition board controlled by a dSPACE MABX 140l. The system can determine the charge/discharge strategy, acquire current, voltage and temperature, and control the charge subsystem and discharge subsystem. A programmable power supply is used as the charger, which can supply up to 60 A with an output voltage of 80 V. A programmable electronic load, which can sink up to 600 A, is utilized as the discharge load. A current sensor with a sensitivity of 1% is also employed. The battery board and the control board are shown in Fig. 17 and Fig. 18, respectively. A. Over charge and over discharge detection verification The over charge fault detection is observed with a constant current charging scheme. The six cells are connected in series. The initial SoC of cell 3 is 80%, while the other cells' initial
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The over discharge fault is induced by discharging an imbalanced string with consecutive UDDS cycles. The initial SoC of cell 3 is 20%, while the other five cells' SoC are 50%. The over discharge fault is detected as shown in Fig. 20.
B. ESC detection validation The test string is discharged by UDDS cycles, until the ESC fault is induced by closing a controlled relay at 180s. The key values are plotted in Fig. 21 where the results show that it takes 15.1 s for this algorithm to detect the occurrence of an ESC as the last condition of temperature increase rate is met at 195.1 s. The temperature increase at detection is 3.67°C.
readings, voltage monitoring is key in determining the safety condition of the battery system, while current and temperature readings are essential to distinguish among the different types of electrical faults.
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