Pulse charging system for lithium ion battery pack

Abstract

A pulse charging system for a lithium ion battery pack includes one or more controllers in electronic communication with the lithium ion battery pack. The one or more controllers include one or more processors that execute instructions to estimate lithium precipitation intensities of the lithium ion battery pack during two or more initial pulse charge cycles thereof. The one or more controllers calculate an updated lithium precipitation intensity of the lithium ion battery pack corresponding to a subsequent pulse charge cycle determined based on the lithium precipitation intensity of the lithium ion battery pack. In response to determining that the updated lithium precipitation intensity falls within the acceptable range of the lithium precipitation intensity value, the one or more controllers perform an optimized pulsed charge cycle based on the updated lithium precipitation intensity.

Description

Technical Field

[0001] This disclosure relates to a pulse charging system for lithium-ion battery packs, which determines multiple pulse charging parameters based on the lithium deposition intensity of the lithium-ion battery pack during pulse charging. Multiple pulse charging parameters are selected to minimize lithium deposition and maximize the charging rate of the lithium-ion battery pack. Background Technology

[0002] Lithium-ion batteries are rechargeable batteries widely used in various applications, such as electric vehicles, portable electronic products like smartphones and digital cameras, and grid storage applications. Several battery charging management strategies are currently available. One commonly used charging strategy is pulse charging, which offers faster charging speeds and reduces lithium deposition compared to some other types of charging methods.

[0003] Lithium deposition refers to the formation of dendrites, primarily composed of metallic lithium, on the anode of a lithium-ion battery, typically occurring under fast-charging conditions and at lower temperatures. To reduce lithium deposition, pulse charging of lithium-ion batteries can be performed based on frequency-designed pulses and rest periods between pulses. However, longer rest periods between pulses increase the total charging time. Another method to reduce the impact of lithium deposition involves detecting it during charging. Several available lithium deposition detection techniques are mentioned in the literature; however, many of these techniques may be impractical or unable to detect lithium deposition in certain types of lithium-ion batteries. For example, some types of lithium deposition detection techniques require relatively long rest periods after charging to determine lithium deposition, rather than detection during the charging cycle. Another alternative is to implement model-based algorithms, which include nonlinear lithium-ion battery models with online calibration capabilities, taking into account the aging characteristics of the battery cells when calculating pulse charging parameters. However, due to their complexity, these lithium-ion battery models may require significant computational resources and may not be easily implemented for lithium deposition detection.

[0004] Therefore, while current pulse charging technology has achieved its intended purpose, there is still a need in the field for an improved method for pulse charging lithium-ion batteries. Summary of the Invention

[0005] According to several aspects, a pulse charging system for a lithium-ion battery pack is disclosed. The pulse charging system includes one or more controllers in electronic communication with the lithium-ion battery pack. The one or more controllers include one or more processors that execute instructions to estimate the lithium plating intensity of the lithium-ion battery pack during two or more initial pulse charging cycles. The one or more controllers estimate multiple pulse charging parameters for the two or more initial pulse charging cycles, including the state-of-charge (SOC) change and interval time of the lithium-ion battery, by minimizing a cost function that generates output based on the SOC intensity. The one or more controllers determine the initial SOC change and initial interval time of the lithium-ion battery during the two or more initial pulse charging cycles using a model-free numerical optimization method based on the cost function. The one or more controllers execute two consecutive pulse charging cycles, including a first pulse charging cycle and a second pulse charging cycle, wherein the first pulse charging cycle is based on the initial SOC change and initial interval time of the lithium-ion battery, and the second pulse charging cycle is based on subsequent SOC changes and subsequent interval times of the lithium-ion battery. The one or more controllers determine a second updated SOC change and a second updated interval time of the lithium-ion battery corresponding to the two consecutive pulse charging cycles using a model-free numerical optimization method. One or more controllers execute subsequent pulse charge cycles based on a second updated state of charge change and a second updated interval of the lithium-ion battery. One or more controllers calculate the updated lithium plating intensity of the lithium-ion battery pack corresponding to the subsequent pulse charge cycle, and in response to determining that the updated lithium plating intensity falls within an acceptable range of the lithium plating intensity value, one or more controllers execute an optimized pulse charge cycle based on the updated lithium plating intensity.

[0006] On the other hand, estimating the lithium plating intensity of a lithium-ion battery pack includes: determining the state of charge of the lithium-ion battery pack and controlling the power supplied to the lithium-ion battery pack to generate two or more initial pulse charging cycles, wherein the state of charge of the lithium-ion battery pack is greater than the pulse charging state of the lithium-ion battery pack to which the applied current pulse is applied.

[0007] On another front, estimating the lithium plating intensity of a lithium-ion battery pack includes estimating the battery impedance of the lithium-ion battery pack for two or more initial pulse charging cycles based on the changes in cell voltage and cell current of the lithium-ion battery during the reduced current mode of the pulse charging cycle.

[0008] On one hand, estimating the lithium plating intensity of a lithium-ion battery pack includes: forming a spline function representing the relationship between the trigger voltage and battery impedance of the lithium-ion battery pack for two or more initial pulse charging cycles, and estimating the lithium plating intensity of the lithium-ion battery pack based on the curvature of the spline function.

[0009] On the other hand, the trigger voltage represents the battery voltage of the lithium-ion battery pack to which a current pulse is applied.

[0010] On the other hand, one or more controllers determine the curvature of the spline function in the following way:

[0011]

[0012] Where k represents the curvature of the spline function, Ω represents the battery impedance of the lithium-ion battery pack, and V trigger This indicates the trigger voltage.

[0013] On the one hand, the lithium plating intensity is equal to the minimum value of the curvature of the spline function.

[0014] On the other hand, the curvature of the spline function is determined based on one or more machine learning algorithms.

[0015] On the other hand, the curvature of the spline function is determined based on the forward Euler method.

[0016] On one hand, the cost function is expressed as:

[0017]

[0018] Where J represents cost, δSOC represents the state of charge change of the lithium-ion battery pack, and T rest Q represents the interval time, β represents the calibrated weighting factor, and Q represents the interval time. pl Indicates lithium plating strength, T charge This indicates the total charging time.

[0019] On the other hand, model-free numerical optimization methods include one of the following: gradient descent, Newton-Raphson method, and Nelder-Mead method.

[0020] On the other hand, the initial state of charge change of lithium-ion batteries is not equal to the subsequent state of charge change, with a difference of at least about 5%.

[0021] On the one hand, the initial interval time differs from the subsequent interval time by at least approximately 5%.

[0022] On the other hand, the acceptable range of lithium plating strength values ​​includes a minimum acceptable lithium plating strength of approximately zero and a maximum lithium plating strength.

[0023] In another aspect, a pulse charging system for a lithium-ion battery pack is disclosed. This pulse charging system includes one or more controllers in electronic communication with the lithium-ion battery pack, wherein the one or more controllers include one or more processors that execute instructions to estimate the lithium plating intensity of the lithium-ion battery pack during two or more initial pulse charging cycles. Estimating the lithium plating intensity of the lithium-ion battery pack includes determining the state of charge (SOC) of the lithium-ion battery pack and controlling the power supplied to the lithium-ion battery pack to generate two or more initial pulse charging cycles, wherein the SOC of the lithium-ion battery pack is greater than the pulse SOC of the lithium-ion battery pack to which a current pulse is applied. The one or more controllers estimate multiple pulse charging parameters for the two or more initial pulse charging cycles, including the SOC change and intermittent time of the lithium-ion battery, by minimizing a cost function for generating output based on the lithium plating intensity. The one or more controllers determine the initial SOC change and initial intermittent time of the lithium-ion battery during the two or more initial pulse charging cycles using a model-free numerical optimization method based on the cost function. One or more controllers execute two consecutive pulse charging cycles, comprising a first pulse charging cycle and a second pulse charging cycle. The first pulse charging cycle is based on the initial state-of-charge change and initial interval of the lithium-ion battery, and the second pulse charging cycle is based on subsequent state-of-charge changes and subsequent intervals of the lithium-ion battery. One or more controllers determine the second updated state-of-charge change and the second updated interval of the lithium-ion battery corresponding to the two consecutive pulse charging cycles using a model-free numerical optimization method. One or more controllers execute the subsequent pulse charging cycle based on the second updated state-of-charge change and the second updated interval of the lithium-ion battery. One or more controllers calculate the updated lithium plating intensity of the lithium-ion battery pack corresponding to the subsequent pulse charging cycle, and in response to determining that the updated lithium plating intensity falls within an acceptable range of lithium plating intensity values, execute an optimized pulse charging cycle based on the updated lithium plating intensity.

[0024] In one aspect, estimating the lithium plating intensity of a lithium-ion battery pack includes estimating the battery impedance of the lithium-ion battery pack for two or more initial pulse charging cycles based on the changes in cell voltage and cell current of the lithium-ion battery during the reduced current mode of the pulse charging cycle.

[0025] On the other hand, estimating the lithium plating intensity of a lithium-ion battery pack includes: forming a spline function representing the relationship between the trigger voltage and battery impedance of the lithium-ion battery pack during two or more initial pulse charging cycles, and estimating the lithium plating intensity of the lithium-ion battery pack based on the curvature of the spline function.

[0026] On the other hand, one or more controllers determine the curvature of the spline function in the following way:

[0027]

[0028] Where k represents the curvature of the spline function, Ω represents the battery impedance of the lithium-ion battery pack, and V trigger This indicates the trigger voltage.

[0029] In one respect, the cost function is expressed as:

[0030]

[0031] Where J represents cost, δSOC represents the state of charge change of the lithium-ion battery pack, and T rest Q represents the interval time, β represents the calibrated weighting factor, and Q represents the interval time. pl Indicates lithium plating strength, T charge This indicates the total charging time.

[0032] In another aspect, a pulse charging system for a lithium-ion battery pack in an all-electric vehicle is disclosed. This pulse charging system includes one or more electric motors powered by the lithium-ion battery pack and one or more controllers in electronic communication with the lithium-ion battery pack and the one or more electric motors. The one or more controllers include one or more processors that execute instructions to estimate the lithium plating intensity of the lithium-ion battery pack during two or more initial pulse charging cycles. Estimating the lithium plating intensity of the lithium-ion battery pack includes determining the state of charge of the lithium-ion battery pack, controlling the power supplied to the lithium-ion battery pack to generate two or more initial pulse charging cycles, wherein the state of charge of the lithium-ion battery pack is greater than the pulse charge state of the lithium-ion battery pack under applied current pulses, estimating the battery impedance of the lithium-ion battery pack during the two or more initial pulse charging cycles based on changes in the cell voltage and cell current of the lithium-ion battery pack during the decreasing current mode of the pulse charging cycle, forming a spline function representing the relationship between the trigger voltage and the battery impedance of the lithium-ion battery pack during the two or more initial pulse charging cycles, and estimating the lithium plating intensity of the lithium-ion battery pack based on the curvature of the spline function. One or more controllers estimate multiple pulse charging parameters for two or more initial pulse charging cycles, including the state-of-charge (SOC) change and pause time of the lithium-ion battery, by minimizing a cost function based on the lithium plating intensity to generate output. One or more controllers determine the initial SOC change and initial pause time of the lithium-ion battery during the two or more initial pulse charging cycles using a model-free numerical optimization method based on the cost function. One or more controllers execute two consecutive pulse charging cycles, comprising a first pulse charging cycle and a second pulse charging cycle, wherein the first pulse charging cycle is based on the initial SOC change and initial pause time of the lithium-ion battery, and the second pulse charging cycle is based on subsequent SOC changes and subsequent pause times of the lithium-ion battery. One or more controllers determine the second updated SOC change and second updated pause time of the lithium-ion battery corresponding to the two consecutive pulse charging cycles using a model-free numerical optimization method. One or more controllers execute subsequent pulse charging cycles based on the second updated SOC change and second updated pause time of the lithium-ion battery. One or more controllers calculate the updated lithium plating intensity of the lithium-ion battery pack corresponding to the subsequent pulse charging cycle and, in response to determining that the updated lithium plating intensity falls within an acceptable range of lithium plating intensity values, execute an optimized pulse charging cycle based on the updated lithium plating intensity.

[0033] Further applications will become apparent from the description provided herein. It should be understood that these descriptions and specific examples are for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0034] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of this disclosure in any way.

[0035] Figure 1 This is an exemplary schematic diagram of a vehicle including the disclosed pulse charging system for a lithium-ion battery pack, according to an exemplary embodiment.

[0036] Figure 2A A graph representing the anode potential of a lithium-ion battery pack during the reduced current mode of a pulse charging cycle, according to an exemplary embodiment, is shown.

[0037] Figure 2B A graph representing the cathode potential of a lithium-ion battery pack during a reduced current mode of a pulse charging cycle, according to an exemplary embodiment, is shown.

[0038] Figure 2C A graph showing the change in cell current of a lithium-ion battery pack during a reduced current mode of a pulse charging cycle, according to an exemplary embodiment, is shown.

[0039] Figure 2D A graph representing the cell voltage of a lithium-ion battery pack according to an exemplary embodiment is shown;

[0040] Figure 3 This is a graph illustrating a plurality of exemplary spline functions according to an exemplary embodiment, each spline function representing the relationship between the trigger voltage and battery impedance of a lithium-ion battery pack during two or more pulse charging cycles.

[0041] Figure 4 This is a process flow diagram illustrating a method for estimating the lithium plating intensity of a lithium-ion battery pack according to an exemplary embodiment; and

[0042] Figure 5 This is a process flowchart illustrating a method for calculating an updated lithium plating strength and determining whether the updated lithium plating strength falls within an acceptable range of the lithium plating strength value, according to an exemplary embodiment. Detailed Implementation

[0043] The following description is merely exemplary in nature and is not intended to limit this disclosure, its application, or its uses.

[0044] Reference Figure 1 An exemplary schematic diagram of a vehicle 10 including the disclosed pulse charging system 12 is shown. The pulse charging system 12 includes one or more controllers 20 in electronic communication with a lithium-ion battery pack 22, one or more voltage sensors 24, one or more current sensors 26, one or more temperature sensors 28, one or more electric motors 30, and an on-board charger 32. In such... Figure 1In the illustrated embodiment, vehicle 10 is an all-electric vehicle that receives all power from one or more electric motors 30 powered by a lithium-ion battery pack 22. One or more voltage sensors 24 monitor the voltage of the lithium-ion battery pack 22 in real time, one or more current sensors 26 monitor the discharge current of the lithium-ion battery pack 22 in real time, and one or more temperature sensors 28 monitor the battery temperature of the lithium-ion battery pack 22 in real time.

[0045] In such Figure 1 In the illustrated embodiment, the on-board charger 32 is electrically connected to the electric vehicle charging station 14. The electric vehicle charging station 14 provides power to charge the lithium-ion battery pack 22. The electric vehicle charging station 14 may include a charging cable 16 electrically coupled to a receiving connector 34 of the vehicle 10. The receiving connector 34 of the vehicle 10 is electrically connected to the on-board charger 32. The on-board charger 32 converts the alternating current (AC) power supplied from the electric vehicle charging station 14 into direct current (DC) power supplied to the lithium-ion battery pack 22. If the electric vehicle charging station 14 provides DC power, the on-board charger 32 can be bypassed and the DC power can be supplied to the lithium-ion battery pack 22.

[0046] It should be understood that vehicle 10 can be any type of vehicle, such as, but not limited to, passenger cars, trucks, SUVs, vans, or motorhomes. It should also be understood that, although... Figure 1 An electric vehicle is shown, but the pulse charging system 12 is not limited to electric vehicles and can be used in any other application that includes lithium-ion battery packs. Some examples of other applications that may include the pulse charging system 12 include, but are not limited to, portable electronic devices such as smartphones and tablets, drones, and aircraft.

[0047] As described below, one or more controllers 20 of the pulse charging system 12 estimate the lithium plating intensity Q of the lithium-ion battery pack 22 after two or more pulse charging cycles. pl Each pulse charging cycle includes an increasing current mode in which a current pulse is applied to the lithium-ion battery pack 22 and a decreasing current mode representing a pause between current pulses. One or more controllers 20 are based on the lithium plating intensity Q of the lithium-ion battery pack 22. pl Calculate multiple pulse charging parameters. In one embodiment, the multiple pulse charging parameters include the state of charge change δSOC of the lithium-ion battery pack 22 during the increased current mode of the pulse charging cycle and the interval time T representing the duration of the decreased current mode of the pulse charging cycle. rest In a non-limiting embodiment, the plurality of pulse charging parameters may further include the charging rate of the lithium-ion battery pack 22.

[0048] It should be understood that multiple pulse charging parameters are selected to minimize lithium deposition within the lithium-ion battery pack 22 while maximizing the charging rate of the lithium-ion battery pack 22. In other words, multiple pulse charging parameters are optimized to minimize lithium deposition within the lithium-ion battery pack 22 and maximize the charging rate, thereby reducing the total time required to charge the lithium-ion battery pack 22. It should also be understood that while this disclosure describes multiple pulse charging parameters to minimize lithium deposition, similar methods can be used to limit or minimize other types of side reactions, such as solid electrolyte interface (SEI) growth.

[0049] Figure 2A The diagram shows an x-axis 36 representing time (in seconds) and an anode potential U of the lithium-ion battery pack 22 during a reduced current mode representing a pulse charging cycle. anode The curve of the y-axis at 38. Figure 2B The diagram shows the x-axis 40 representing time and the cathode potential U of the lithium-ion battery pack 22 during the reduced current mode representing a pulse charging cycle. cathode The curve with y-axis 42. Figure 2C A graph is shown that includes an x-axis 44 representing time and a y-axis 46 representing the cell current of the lithium-ion battery pack 22, showing the change ΔI of the cell current of the lithium-ion battery pack 22 during the reduced current mode of the pulse charging cycle. Figure 2D A graph is shown that includes an x-axis 48 representing time and a y-axis 50 representing the cell voltage of the lithium-ion battery pack 22, wherein the cell voltage of the lithium-ion battery pack 22 decreases or changes by ΔV during the reduced current mode of the pulse charging cycle.

[0050] Reference Figures 2A-2D It should be understood that, due to various mechanisms triggered after the lithium deposition mechanism (e.g., lithium stripping, also known as stripped lithium), the cell voltage change ΔV of the lithium-ion battery pack 22 decreases during the reduced current mode of the pulse charging cycle. Lithium stripping refers to the detached lithium fragments from the lithium deposited on the anode electrode of the lithium-ion battery pack 22. It should be understood that the cell voltage change ΔV of the lithium-ion battery pack 22 is first measured, and then the battery impedance Ω of the lithium-ion battery pack 22 is estimated. The battery impedance Ω is estimated as the cell voltage ΔV of the lithium-ion battery pack 22 divided by the cell current ΔI during the reduced current mode of the pulse charging cycle, or...

[0051] Figure 3 This is a graph showing multiple exemplary spline function curves (hereinafter referred to as spline lines) 56, each spline line 56 representing the trigger voltage V of the lithium-ion battery pack 22 during four pulse charging cycles. trigger The relationship with the battery cell impedance Ω. Trigger voltage V. triggerThis graph represents the cell voltage of the lithium-ion battery pack 22 under the applied current pulse. Specifically, the graph includes a representation of the trigger voltage V. trigger The x-axis 52 and the y-axis 54 represent the battery impedance Ω of the lithium-ion battery pack 22. Each spline 56 corresponds to a specific time rate or c-rate taken to charge the lithium-ion battery pack 22, where spline 56A represents two or more pulse charging cycles at a c-rate of C / 3, spline 56B represents two or more pulse charging cycles at a c-rate of 0.64C, spline 56C represents two or more pulse charging cycles at a c-rate of 1C, and spline 56D represents two or more pulse charging cycles at a c-rate of 1.2C, where C represents the battery capacity. It should be understood that, although Figure 3 Multiple splines 56 are shown, but the trigger voltage V of the lithium-ion battery pack 22 is... trigger The relationship between the battery impedance Ω and the battery impedance Ω can also be represented by any other continuous function (such as a polynomial).

[0052] It should be understood that as the C rate increases, the lithium plating intensity Q of the lithium-ion battery pack 22 increases. pl It also increases. It should also be understood that as the curvature of splines 56A, 56B, 56C, and 56D increases in the negative direction, the lithium plating intensity Q of the lithium-ion battery pack 22 also increases. pl It also increases. For example, spline 56A, representing a c-rate of C / 3, has a normalized curvature of approximately 0, while spline 56D, representing a c-rate of 1.2C, has a normalized curvature of approximately -0.15.

[0053] The lithium plating strength Q of the estimated lithium-ion battery pack 22 will now be described. pl The method. It should be understood that the lithium plating intensity Q of the lithium-ion battery pack 22... pl If the value is 0, a random perturbation can be applied in the direction of increasing the pulse charging rate. Figure 4 This shows the lithium plating intensity Q used to estimate the lithium-ion battery pack 22 during its two or more initial pulse charge cycles. pl The process flowchart for Method 400 is shown below. (Refer to...) Figure 1 and Figure 4 Method 400 may begin at block 402. In block 402, one or more controllers 20 determine the state of charge of the lithium-ion battery pack 22. Method 400 may then proceed to block 404.

[0054] In block 404, one or more controllers 20 control the power supplied from the electric vehicle charging station 14 to the lithium-ion battery pack 22 to generate two or more initial pulse charging cycles. As described above, each pulse charging cycle includes a current-increasing mode in which a current pulse is applied to the lithium-ion battery pack 22 and a current-decreasing mode representing a pause between the current pulses applied in the current-increasing mode. The state of charge (SOC) of the lithium-ion battery pack 22 is greater than the pulse charge SOC of the lithium-ion battery pack 22 at the time the current pulse is applied, or SOC > SOC. pulse SOC pulse This indicates the state of charge when the current pulse is applied, and SOC indicates the state of charge of the lithium-ion battery pack 22. Then method 400 can proceed to block 406.

[0055] In block 406, one or more controllers 20 estimate the battery impedance Ω of the lithium-ion battery pack 22 for two or more initial pulse charging cycles based on the battery voltage change ΔV of the lithium-ion battery pack 22 during the reduced current mode of a single pulse charging cycle and the battery current change ΔI of the lithium-ion battery pack 22 during the reduced current mode of the initial pulse charging cycle. Specifically, as described above, the battery impedance Ω is the battery voltage change ΔV of the lithium-ion battery pack 22 during the reduced current mode of the initial pulse charging cycle divided by the battery current ΔI, or... Then method 400 can proceed to box 408.

[0056] In box 408, one or more controllers 20 form spline 56 (see...). Figure 3 The spline 56 represents the trigger voltage V of the lithium-ion battery pack 22 during two or more initial pulse charging cycles. trigger The relationship between the battery impedance Ω and the impedance. Then method 400 can proceed to box 410.

[0057] In box 410, one or more controllers 20 are based on spline 56 defined in box 408. Figure 3 The curvature of the lithium-ion battery pack 22 is used to estimate the lithium plating intensity Q. pl The following describes several methods for determining the curvature of spline 56. Method 400 can then be terminated.

[0058] Reference Figure 1 and Figure 3 In one embodiment, the curvature of spline 56 is determined by first calculating the curvature of the spline function based on Equation 1, which is:

[0059]

[0060] Where k represents the curvature of spline 56. Once the curvature of spline 56 is known, one or more controllers 20 solve for the relationship between the curvature of spline 56 and the lithium plating intensity Q.pl The associated continuous function f(k). Specifically, the lithium plating intensity Q pl The minimum curvature of spline 56 is equal to that of spline 56, which is expressed in Equation 2 as:

[0061] f(k)=|min ([k1,k2,…],0| Equation 2

[0062] Where, k i It is the curvature at sampling point i.

[0063] It should be understood that other methods can also be used to determine the curvature of spline 56. For example, in another embodiment, the curvature of spline 56 can be estimated based on one or more numerical methods (e.g., the forward Euler method). Specifically, the forward Euler method can be used to solve the first and second derivatives in Equation 1 to determine the curvature of spline 56. In another embodiment, the curvature of spline 56 can be determined based on one or more machine learning algorithms, such as, but not limited to, convolutional neural networks (CNNs) or long short-term memory (LSTM) neural networks.

[0064] Reference Figure 1 Once the lithium plating strength Q is determined pl One or more controllers 20 of the pulse charging system 12 minimize the lithium plating intensity Q pl and charging time T charge The cost function that generates the output is used to estimate multiple pulse charging parameters for two or more initial pulse charging cycles, where the charging time T charge This represents the total charging time. Specifically, multiple pulse charging parameters include the increased current mode and the interval time T during the initial pulse charging cycle. rest The state of charge (SOC) of the lithium-ion battery pack 22 during this period varies. In one embodiment, the cost function is expressed in Equations 3-7 as follows:

[0065]

[0066] Make:

[0067] T charge =α1T rest +α2(100-δSOC) Equation 4

[0068] δSOC max >δSOC>0 Equation 5

[0069] Q pl ≥Q pl-min Formula 6

[0070] T rest ≥0 Equation 7

[0071] Where J represents cost, used to find the increasing current pattern and interval time T during the initial pulse charging cycle. rest The value corresponding to the change in state of charge δSOC of lithium-ion battery pack 22 during the period, where β represents the calibrated weighting factor, α1 represents the first adjustment parameter, and α2 represents the second adjustment parameter, δSOC max Q represents the maximum permissible change in the state of charge δSOC of the lithium-ion battery pack 22 during the increased current mode of the initial pulse charging cycle. pl-min This indicates the minimum permissible lithium plating intensity of the lithium-ion battery pack 22.

[0072] Then, one or more controllers 20 determine the first updated state-of-charge change δSOC of the lithium-ion battery pack 22 during the increased current mode of two or more initial pulse charging cycles. new The first update interval T of the reduced current mode during two or more initial pulse charging cycles. rest,new The initial state of charge change δSOC0 of the lithium-ion battery pack 22 during the increased current mode of the first continuous pulse charging cycle, and the initial interval time T during the decreased current mode of the first continuous pulse charging cycle. rest,0 The first update of the state of charge change δSOC of the lithium-ion battery pack 22 new and the first update interval T rest,new Indicated based on Figure 4 The lithium plating strength Q determined in method 400 is shown. pl And the determined charging parameters.

[0073] The first update of the state of charge change δSOC of the lithium-ion battery pack 22 new First update interval T rest,new The initial state of charge change δSOC0 and the initial interval time T of the lithium-ion battery pack 22 rest,0 The cost is determined by a model-free numerical optimization method based on a cost function that generates the output based on the lithium plating intensity, as described in Equation 3. Examples of model-free numerical optimization methods include, but are not limited to, gradient descent, the Newton-Raphson method, or the Nelder-Mead method. In the example described below, the gradient descent method is used to determine the first updated state-of-charge change δSOC of the lithium-ion battery pack 22. new First update interval T rest,new The initial state of charge change δSOC0 of the lithium-ion battery pack 22, and the initial interval time T rest,0 In Equation 8-14, it is expressed as:

[0074]

[0075] Assuming lithium plating strength Qpl Relative to the interval time T rest Gradient and lithium plating intensity Q pl The gradient linear correlation with the state of charge δSOC is expressed in Equation 12 as follows:

[0076]

[0077] Then

[0078]

[0079] in, This represents the gradient of the cost function with respect to the change in the state of charge δSOC of the lithium-ion battery pack 22. The cost function is expressed relative to the interval time T. rest The gradient, Γ represents the linear correlation factor, β sOC For use in calculating SOC new The adjustment parameter β of the gradient method T Based on the interval time T rest Adjust the parameters.

[0080] Once the first update state of charge change δSOC of the lithium-ion battery pack 22 new First update interval T rest,new The initial state of charge change δSOC0 of the lithium-ion battery pack 22, and the initial interval time T rest,0 Once determined, one or more controllers 20 execute two consecutive pulse charging cycles. Specifically, the two consecutive pulse charging cycles include a first pulse charging cycle and a second pulse charging cycle. The first pulse charging cycle is based on the initial state of charge change δSOC0 of the lithium-ion battery pack 22 and the initial interval time T. rest,0 Furthermore, the second pulse charging cycle is based on the subsequent state-of-charge change δSOC1 of the lithium-ion battery pack 22 and the subsequent interval time T. rest,1 The initial state-of-charge change δSOC0 of the lithium-ion battery pack 22 is not equal to the subsequent state-of-charge change δSOC1, with a difference of at least approximately 5%. Similarly, the initial interval time T... rest,0 With subsequent interval T rest,1 The difference is at least approximately 5%.

[0081] Figure 5 This shows the method used to calculate the updated lithium plating strength Q. pl_new And determine the updated lithium plating strength Q pl_new The process flow diagram for method 500, which determines whether the lithium plating strength value falls within an acceptable range, is shown. In response to determining and updating the lithium plating strength Q... pl_new If the lithium plating strength value falls within an acceptable range, one or more controllers 20 can then execute an update based on the lithium plating strength Q.pl_new Optimized pulse charging cycle. (Refer to...) Figure 1 and Figure 5 Method 500 may begin at block 502. In block 502, one or more controllers 20 execute two consecutive pulse charging cycles. Method 500 may then proceed to block 504.

[0082] In block 504, one or more controllers 20 calculate the first lithium plating intensity Q corresponding to the first pulse charging cycle of two consecutive pulse charging cycles. pl_0 And the second lithium plating intensity Q corresponding to the second pulse charging cycle of two consecutive pulse charging cycles. pl_1 The method used to determine the lithium plating intensity is described above and shown as follows. Figure 4 Method 400. Then method 500 can proceed to box 506.

[0083] In block 506, one or more controllers 20 are based on the lithium plating intensity variation of two consecutive pulse charging cycles. and the change in the interval time between two consecutive pulse charging cycles To calculate the lithium plating intensity gradient between two consecutive pulse charging cycles. Lithium plating intensity change The first lithium plating strength Q pl_0 Second lithium plating strength Q pl_1 The difference between them, and the variation in interval time. The first interval time T rest1 Second interval T rest0 The difference between them. Lithium plating intensity gradient. It is the change in lithium plating intensity Divide by the change in interval time or Then method 500 can proceed to box 508.

[0084] In block 508, one or more controllers 20 determine a second updated state-of-charge change δSOC of the lithium-ion battery pack 22 during an increased current mode of two or more consecutive pulse charging cycles. new The second update interval T during the reduced current mode of two consecutive pulse charging cycles rest,new The second initial state of charge change δSOC0 of the lithium-ion battery pack 22 during the increased current mode of subsequent pulse charging cycles, and the lithium plating intensity gradient calculated based on block 506 and Equation 3-14 above. The second initial interval T of the reduced current mode in the subsequent pulse charging cycle rest,0 Then method 500 can proceed to box 510.

[0085] In box 510, one or more controllers 20 then update the state of charge change δSOC of the lithium-ion battery pack 22 based on a second update. new and the second update interval T determined in box 508 rest,new This will execute the subsequent pulse charging cycle. Then method 500 can proceed to block 512.

[0086] In box 512, one or more controllers 20 are based on Figure 4 The method 400 shown determines the updated lithium plating intensity Q corresponding to subsequent pulse charging cycles. pl_new Then, one or more controllers 20 can adjust the initial lithium plating intensity Q. pl_0 Set to equal to the subsequent lithium plating strength Q pl_1 And the subsequent lithium plating strength Q pl_1 Set to equal the updated lithium plating strength Q pl_new Then method 500 can proceed to decision box 514.

[0087] In decision box 514, one or more controllers 20 will update the lithium plating intensity Q. pl_new Compare with the acceptable range of lithium plating strength values. The acceptable range of lithium plating strength values ​​includes a minimum acceptable lithium plating strength Q equal to approximately zero. pl_min and the maximum lithium plating strength Q determined by the manufacturer of the lithium-ion battery pack 22 or the vehicle manufacturer. pl_max In response to determining the updated lithium plating strength Q pl_new If the lithium plating strength value does not fall within an acceptable range, method 500 returns to box 506. In response to determining the updated lithium plating strength Q... pl_new If the lithium plating intensity value falls within an acceptable range, method 500 can then proceed to block 516.

[0088] In block 516, one or more controllers 20 execute one or more optimized pulse charging cycles. The one or more optimized pulse charging cycles include operations based on the updated lithium plating strength Q. pl_new Several optimized pulse charging parameters are determined. One or more optimized pulse charging parameters minimize lithium deposition within the lithium-ion battery pack 22 while maximizing the charging rate of the lithium-ion battery pack 22. Method 500 can then return to block 510.

[0089] Referring generally to the accompanying drawings, the disclosed pulse charging system offers various technical effects and benefits. Specifically, the pulse charging system provides a numerical method for estimating the lithium plating intensity of a lithium-ion battery pack based on the change in battery voltage when the lithium-ion battery pack is pulse-charged. The lithium plating intensity of the lithium-ion battery pack is used to determine multiple pulse charging parameters, which are optimized to minimize lithium plating within the lithium-ion battery cells and maximize the charging rate, thereby reducing the total time required to charge the lithium-ion battery cells.

[0090] A controller can refer to electronic circuitry, combinational logic circuitry, a field-programmable gate array (FPGA), a processor (shared, dedicated, or grouped) that executes code, or a portion of electronic circuitry, combinational logic circuitry, a FPGA, or a combination thereof (e.g., in a system-on-a-chip). Additionally, the controller can be microprocessor-based, such as a computer having at least one processor, memory (RAM and / or ROM), and associated input and output buses. The processor can operate under the control of an operating system residing in memory. The operating system can manage computer resources such that computer program code embodied as one or more computer software applications (e.g., applications residing in memory) can have instructions that are executed by the processor. In alternative embodiments, the processor can directly execute the application, in which case the operating system can be omitted.

[0091] The descriptions in this disclosure are merely exemplary in nature, and variations thereof that do not depart from the spirit and scope of this disclosure are intended to fall within its scope. Such variations should not be considered as departing from the spirit and scope of this disclosure.

Claims

1. A pulse charging system for a lithium-ion battery pack, the pulse charging system comprising: One or more controllers, in electronic communication with the lithium-ion battery pack, wherein the one or more controllers include one or more processors that execute instructions to: Estimate the lithium plating intensity of the lithium-ion battery pack during its two or more initial pulse charging cycles; Multiple pulse charging parameters for the two or more initial pulse charging cycles are estimated by minimizing the cost function that generates the output based on the lithium plating intensity. These multiple pulse charging parameters include the state of charge change and interval time of the lithium-ion battery. The initial state of charge change and initial interval time of the lithium-ion battery during the two or more initial pulse charging cycles are determined by a model-free numerical optimization method based on the cost function. Two consecutive pulse charging cycles are executed, the two consecutive pulse charging cycles including a first pulse charging cycle and a second pulse charging cycle, wherein the first pulse charging cycle is based on the initial state of charge change of the lithium-ion battery and the initial interval time, and the second pulse charging cycle is based on the subsequent state of charge change of the lithium-ion battery and the subsequent interval time. The second updated state of charge change and the second update interval time of the lithium-ion battery corresponding to the two consecutive pulse charging cycles are determined by the model-free numerical optimization method. The subsequent pulse charging cycle is executed based on the second updated state of charge change of the lithium-ion battery and the interval of the second update; Calculate the renewed lithium plating intensity of the lithium-ion battery pack corresponding to the subsequent pulse charging cycle; as well as In response to determining that the updated lithium plating intensity falls within an acceptable range of the lithium plating intensity value, an optimized pulse charging cycle based on the updated lithium plating intensity is performed.

2. The pulse charging system according to claim 1, wherein, The lithium plating intensity of the lithium-ion battery pack is estimated as follows: Determine the state of charge of the lithium-ion battery pack; and The power supplied to the lithium-ion battery pack is controlled to generate the two or more initial pulse charging cycles, wherein the state of charge of the lithium-ion battery pack is greater than the pulse charging state of the lithium-ion battery pack under the applied current pulse.

3. The pulse charging system according to claim 2, wherein, The lithium plating intensity of the lithium-ion battery pack is estimated as follows: The battery impedance of the lithium-ion battery pack during the two or more initial pulse charging cycles is estimated based on the changes in battery voltage and battery current of the lithium-ion battery during the reduced current mode of the pulse charging cycle.

4. The pulse charging system according to claim 3, wherein, The lithium plating intensity of the lithium-ion battery pack is estimated as follows: Form a spline function representing the relationship between the trigger voltage and the battery impedance of the lithium-ion battery pack during the two or more initial pulse charging cycles; and The lithium plating intensity of the lithium-ion battery pack is estimated based on the curvature of the spline function.

5. The pulse charging system according to claim 4, wherein, The trigger voltage represents the battery voltage of the lithium-ion battery pack to which a current pulse is applied.

6. The pulse charging system according to claim 4, wherein, The one or more controllers determine the curvature of the spline function in the following manner: Where k represents the curvature of the spline function, Ω represents the battery impedance of the lithium-ion battery pack, and V trigger This indicates the trigger voltage.

7. The pulse charging system according to claim 6, wherein, The lithium plating intensity is equal to the minimum curvature of the spline function.

8. The pulse charging system according to claim 4, wherein, The curvature of the spline function is determined based on one or more machine learning algorithms.

9. The pulse charging system according to claim 4, wherein, The curvature of the spline function is determined based on the forward Euler method.

10. The pulse charging system according to claim 1, wherein, The cost function is expressed as: Where J represents the cost, δSOC represents the state of charge change of the lithium-ion battery pack, and T rest The interval time is represented by β, and the calibrated weighting factor is Q. pl T represents the lithium plating intensity. charge This indicates the total charging time.

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