Electric vehicle battery capacity and related control

Abstract

The present disclosure provides'electric vehicle battery capacity and related control '. An automotive power control system modifies a maximum discharge power of a traction battery as a function of an estimated capacity of the traction battery. The estimated capacity depends on a set of previous instantaneous capacity values of the traction battery and a current instantaneous capacity value of the traction battery. The total number of the previous instantaneous capacity value and the current instantaneous capacity value depends on the state of charge of the traction battery at two different moments in time.

Description

Technical Field

[0001] The present disclosure relates to estimating traction battery capacity of an electric vehicle (EV) and related control operations. Background Art

[0002] Electric vehicles rely on traction batteries to supply power to the electric motor for propulsion. Over time, the capacity of the traction battery may decrease. The onboard vehicle computer can be configured to update the battery capacity. Summary of the Invention

[0003] A vehicle includes a traction battery, an electric motor, a switch electrically connecting the traction battery and the electric motor, and a controller. The controller modifies a maximum discharge power of the traction battery based on an estimated capacity of the traction battery, the estimated capacity being dependent on a set of previous instantaneous capacity values ​​of the traction battery and a current instantaneous capacity value of the traction battery, such that a sum of the previous instantaneous capacity values ​​and the current instantaneous capacity value is dependent on a state of charge of the traction battery when the switch is closed.

[0004] A method includes modifying a maximum discharge power of a traction battery based on an estimated capacity of the traction battery, the estimated capacity being dependent on a set of previous instantaneous capacity values, the size of the set of previous instantaneous capacity values ​​being dependent on a state of charge of the traction battery at a first time instance and a second time instance.

[0005] A vehicle power control system includes a controller configured to modify a maximum discharge power of a traction battery based on an estimated capacity of the traction battery. The estimated capacity is dependent on a set of previous instantaneous capacity values ​​of the traction battery and a current instantaneous capacity value of the traction battery. The sum of the previous instantaneous capacity values ​​and the current instantaneous capacity value is dependent on a state of charge of the traction battery at a first time instance and a second time instance. BRIEF DESCRIPTION OF THE DRAWINGS

[0006] Figure 1 An example block topology of an electrified vehicle is shown, illustrating the powertrain and energy storage components.

[0007] Figure 2 An example flow chart of a process for operating a vehicle is shown. DETAILED DESCRIPTION

[0008] Embodiments are described herein. However, it should be understood that the disclosed embodiments are merely examples and that other embodiments may take various and alternative forms. The drawings are not necessarily drawn to scale. Some features may be exaggerated or minimized to illustrate details of particular components. Therefore, the specific structural and functional details disclosed herein should not be construed as limiting, but merely as a representative basis for teaching those skilled in the art.

[0009] The various features shown and described with reference to any one of the accompanying drawings may be combined with features shown in one or more other drawings to produce embodiments not explicitly shown or described. The combinations of features shown provide representative embodiments for typical applications. However, for specific applications or implementations, various combinations and modifications of features may be desired consistent with the teachings of this disclosure.

[0010] The present disclosure relates particularly to a method and system for estimating the capacity of a traction battery of an EV. More specifically, the present disclosure relates to a method and system for determining an appropriate sample size for a moving average filter configured to estimate battery capacity.

[0011] Figure 1 A plug-in hybrid electric vehicle (PHEV) is shown. The plug-in hybrid electric vehicle 112 may include one or more electric motors (electric motors) 114 mechanically coupled to a hybrid transmission 116. The electric motor 114 may be capable of operating as a motor or a generator. In addition, the hybrid transmission 116 is mechanically coupled to an engine 118. The hybrid transmission 116 is also mechanically coupled to a drive shaft 120, which is mechanically coupled to wheels 122. The electric motor 114 can provide propulsion and deceleration capabilities when the engine 118 is turned on or off. The electric motor 114 can also act as a generator and can provide fuel economy benefits by recovering energy lost as heat in the friction braking system. The electric motor 114 can also reduce vehicle emissions by allowing the engine 118 to operate at a more efficient speed and allowing the hybrid electric vehicle 112 to be operated in electric mode under certain conditions when the engine 118 is turned off.

[0012] The traction battery or battery pack 124 stores energy that can be used by the electric motor 114. The vehicle battery pack 124 can provide a high-voltage DC output. The traction battery 124 can be electrically coupled to one or more battery electric control modules (BECMs) 125. The BECMs 125 can be equipped with one or more processors and software applications configured to monitor and control various operations of the traction battery 124. The traction battery 124 can also be electrically coupled to one or more power electronics modules 126. Power electronics modules 126 can also be referred to as power inverters. One or more contactors 127 can isolate the traction battery 124 and BECM 125 from other components when open, and connect the traction battery 124 and BECM 125 to other components when closed. The power electronics modules 126 can also be electrically coupled to the electric motor 114 and provide bidirectional energy transfer between the traction battery 124 and the electric motor 114. For example, the traction battery 124 can provide a DC voltage, while the electric motor 114 can operate using three-phase AC current. The power electronics module 126 can convert the DC voltage into three-phase AC current for use by the motor 114. In regenerative mode, the power electronics module 126 can convert the three-phase AC current from the motor 114, which acts as a generator, into a DC voltage compatible with the traction battery 124. The description herein is equally applicable to pure electric vehicles. For pure electric vehicles, the hybrid transmission 116 can be a gearbox connected to the motor 114, and the engine 118 may not be present.

[0013] In addition to providing energy for propulsion, the traction battery 124 can also provide energy for other vehicle electrical systems. The vehicle includes a DC / DC converter module 128 that converts the high-voltage DC output of the traction battery 124 into a low-voltage DC supply compatible with other low-voltage vehicle loads. The output of the DC / DC converter module 128 can be electrically coupled to an auxiliary battery 130 (e.g., a 12V battery).

[0014] The vehicle 112 may be a battery electric vehicle (BEV) or a plug-in hybrid electric vehicle (PHEV), wherein the traction battery 124 may be recharged by an external power source 136. The external power source 136 may be a connection to an electrical outlet. The external power source 136 may be a distribution network or grid provided by an electric utility company. The external power source 136 may be electrically coupled to an electric vehicle supply equipment (EVSE) 138. The EVSE 138 may provide circuitry and controls to manage energy transfer between the power source 136 and the vehicle 112. The external power source 136 may provide DC or AC power to the EVSE 138. The EVSE 138 may have a charging connector 140 for plugging into a charging port 134 of the vehicle 112. The charging port 134 may be any type of port configured to transfer power from the EVSE 138 to the vehicle 112. The charging port 134 may be electrically coupled to a charger or an onboard power conversion module 132. The power conversion module 132 can condition the power supplied from the EVSE 138 to provide appropriate voltage and current levels to the traction battery 124. The power conversion module 132 can interact with the EVSE 138 to coordinate the delivery of power to the vehicle 112. The EVSE connector 140 can have pins that mate with corresponding recesses of the charging port 134. Alternatively, the various components described as being electrically coupled can use wireless inductive coupling to transfer power.

[0015] One or more electrical loads 146 may be coupled to the high voltage bus. The electrical loads 146 may have associated controllers that operate and control the electrical loads 146 as appropriate. Examples of electrical loads 146 may be heating modules, air conditioning modules, and the like.

[0016] The various components discussed may have one or more associated controllers to control and monitor the operation of the components. The controllers may communicate via a serial bus (e.g., a controller area network (CAN)) or via discrete conductors. A system controller 150 may be present to coordinate the operation of the various components. It should be noted that the system controller 150 is used as a general term and may include one or more controller devices configured to perform the various operations in this disclosure. For example, the system controller 150 may be programmed to enable powertrain control functions to operate the powertrain of the vehicle 112. The system controller 150 may also be programmed to enable telecommunication functions with various entities (e.g., servers) via a wireless network (e.g., a cellular network).

[0017] The BECM 125 can be configured to perform various operations. For example, the BECM 125 can be configured to periodically perform capacity estimation of the traction battery 124. As described above, over time, the total capacity of the traction battery 124 may decrease. After a period of time, the true capacity (actual capacity or updated capacity) of the traction battery 124 may be less than the design capacity of the traction battery 124 when it was manufactured. Accurate determination of the actual capacity can facilitate operation and control of the vehicle 112. For example, accurate estimation of the actual capacity can provide vehicle users with better range estimates and charging and discharging operations.

[0018] There are a variety of methods to determine the actual capacity of the traction battery 124. In the present disclosure, the BECM 125 may be configured to determine the actual capacity of the traction battery 124 using a moving average filter that estimates the true capacity Q of the traction battery 124 by determining the average of multiple instantaneous capacities. True , the multiple instantaneous capacities include multiple previously calculated capacities Q Old (previous capacity or old capacity) and the newly calculated capacity Q new (new capacity). The moving average filter can be expressed as the following equation:

[0019]

[0020] In the above equation (1), N represents the sample size, which includes the previously calculated capacity Q Old and the newly calculated capacity Q New More specifically, the sample size N may be an integer defining the total number of instantaneous capacity data points comprising the previously determined capacity Q Old and the newly calculated instantaneous capacity Q New Both are considered to estimate the real capacity Q of the traction battery 124 True The moving average filter expressed in equation (1) above requires N-1 previously calculated capacities Q Old and a newly calculated capacity Q New To determine the true capacity Q of the traction battery True The previously calculated capacity Q Old may be stored in a non-volatile manner in an onboard storage device associated with the BECM 125. Although a larger sample size N makes the true capacity estimate more accurate, a larger sample size requires more storage space to store the previously calculated capacity Q Old(and their associated data), and increases computational complexity that affects the performance of the moving average filter. As a result, the BECM 125 may be slow to keep up with degradation updates with large sample sizes N. Conversely, smaller sample sizes may introduce more noise to the filter, making the true capacity estimate less accurate.

[0021] The present disclosure proposes a method for determining an appropriate sample size N that strikes a balance between the accuracy of the true capacity estimation of the vehicle 112 and the hardware requirements. More specifically, the present disclosure determines the sample size N based on the assumption that battery degradation is a slow process and that the true capacity of the traction battery does not change significantly over a short period of time (e.g., one month). In contrast, the true instantaneous capacity Q True It can be approximately equal to the predetermined average capacity Q Avg (e.g., via previous calculations or via a lookup table.) For example, the lookup table may be stored in a non-volatile manner within the memory of the BECM 125 and / or memory associated with other components of the vehicle 112. The average capacity Q may be adjusted via the uncertainty component. Avg To determine the actual capacity Q of the traction battery 124 True More specifically, the actual capacity Q of the traction battery 124 True This can be expressed using the following equation:

[0022]

[0023] Where U(Q New ) represents the newly calculated instantaneous capacity Q with the most recent estimate New Associated uncertainty.

[0024] The above equation (2) can be further developed as follows:

[0025]

[0026] Due to the average uncertainty of the average capacity U Avg It can be defined as the difference between the actual capacity and the average capacity of the traction battery 124 (e.g., Q True –Q Avg ), so the above equation (3) can be further developed as:

[0027]

[0028] Uncertainty of average capacity U Avg It can be a predetermined goal or objective based on design needs. For example, the acceptable average capacity uncertainty U Avg Can be set in the range of 1% to 5%. Additionally or alternatively, the average capacity uncertainty U AvgIt may vary depending on one or more factors such as battery charge cycles, battery age, etc. For example, when the battery is new, the acceptable average capacity uncertainty U Avg As the battery ages and accumulates more charge cycles, the acceptable average capacity uncertainty U Avg May increase.

[0029] Since the average uncertainty U of the moving average filter Avg has become available or determined, so the only parameter used to determine the sample size N is the newly calculated instantaneous capacity U(Q New The present disclosure proposes a method for determining a new instantaneous capacity U(Q) corresponding to the most recently calculated capacity based on the estimated state of charge (SOC) and ampere-hour integration of the traction battery 124. New More specifically, the uncertainty of the estimated new instantaneous capacity U(Q New ) can be determined by:

[0030]

[0031] in Represents the integral of the current (e.g., net ampere-hour throughput) between a first time instance when the main contactor 127 is closed and a subsequent second time instance when the main contactor 127 is closed. Both the first instance and the second instance can be time points before the current time. The time period between the first instance and the second instance only includes the amount of time when the main contactor 127 is closed. As an example, the first instance may occur at 8:00 a.m. when the vehicle 112 is driven from the user's home to work for one hour. The vehicle may be parked for 8 hours and then driven home at 5:00 p.m., which takes another hour. The second instance may occur when the vehicle 112 is plugged in at home at 6:00 p.m. In the above example, the total time is 2 hours (excluding the 8 hours of parking time).

[0032] represents the uncertainty associated with the net amp-hour throughput measurement as calculated via current integration. The traction battery 124 may be coupled with a predetermined current sensor uncertainty U in the form of an amp-hour error per hour. Sensor For example, if the current sensor has an uncertainty U of 3Ah per hour Sensor , then an uncertainty of up to 3Ah may apply after 1 hour of measurement. Therefore, the uncertainty associated with the net amp-hour throughput measurement can be determined using the following equation:

[0033]

[0034] In one example, the current sensor uncertainty USensor Can be a constant. Alternatively, the current sensor uncertainty U Sensor Can be a variable that is a function of current or other factors.

[0035] SOC LUT (V(CC1), T(CC1)) represents the SOC of the traction battery 124 estimated via the SOC-OCV lookup table in the first instance. LUT (V(CC2), T(CC2)) represents the SOC of the traction battery 124 estimated at the second instance via the SOC-OCV lookup table. The SOC-OCV lookup table may be stored in a non-volatile manner within the memory of the BECM 125 and / or memory associated with other components of the vehicle 112. Like most other lookup tables, the SOC-OCV lookup table may not be 100% accurate. Therefore, the SOC-OCV lookup process may be inherently associated with uncertainty. Equation (5) above is improved by introducing U(SOC2) which reflects the uncertainty associated with the SOC-OCV lookup process at the first instance. LUT (V(CC1), T(CC1))) and U(SOC) reflecting the uncertainty associated with the SOC-OCV lookup process at the second instance LUT (V(CC2),T(CC2))) to take uncertainty into account.

[0036] The newly calculated instantaneous capacity Q presented in equation (5) above can be calculated using the following equation New :

[0037]

[0038] With all required parameters determined, the sample size N of the moving average filter can be estimated using equation (4) above. Thus, the BECM 125 can determine the true capacity Q of the traction battery 124 by applying the determined sample size N to equation (1). True .

[0039] refer to Figure 2 , shows an example process 200 for operating a vehicle. Figure 1 , process 200 may be independently implemented via the BECM 125. Additionally or alternatively, process 200 may be implemented collectively via the BECM 125, the system controller 150, and / or other components of the vehicle 112 under substantially the same concepts. For simplicity, the following description will refer to the BECM 125. At operation 202, the BECM 125 determines the average capacity Q of the traction battery 124 based on one or more parameters. AvgAs discussed above, the average capacity Q can be determined via a lookup table based on parameters such as battery age and charge cycles. Avg At operation 204 , the BECM 125 determines the target average capacity uncertainty U Avg In one example, the average capacity Q may be determined based on the average capacity Q previously determined at operation 202. Avg To determine the target uncertainty. As the traction battery 124 ages and the charge cycles increase, the target uncertainty U Avg Alternatively, the target average capacity uncertainty U Avg can be independent of the average capacity Q of the traction battery 124 Avg In contrast, the target average capacity uncertainty U Avg It may be set by a user (or technician) and received by the vehicle 112 (eg, via an interface).

[0040] At operation 206 , the BECM 125 estimates the most recent instantaneous capacity Q of the traction battery 124 based on the ampere-hour integral and SOC for both the first and second instances of the previous main contactor closure using equation (8) above. New A lookup table may be used to determine the SOC using the voltage and temperature measured at the corresponding instance as inputs. At operation 208 , the BECM 125 estimates the SOC corresponding to the most recent instantaneous capacity Q using equation (5) discussed above. New The associated uncertainty U(Q New ).

[0041] At operation 210 , the BECM 125 calculates the capacity uncertainty U based on the average capacity uncertainty U avg and the most recent instantaneous capacity Q new The associated uncertainty U(Q new ) uses equation (4) discussed above to estimate the sample size N. With the appropriate sample size N estimated, at operation 212, the BECM 125 loads N-1 previously determined capacities Q from the onboard storage device. Old At operation 214 , the BECM 125 uses the N instantaneous capacities to estimate the true capacity Q of the traction battery based on equation (1) presented above. True More specifically, the BECM 125 may use the most recent instantaneous capacity Q New and (N-1) previously determined capacities Q Old As the input sample of equation (1) to determine the real capacity Q True .

[0042] After determining the actual capacity Q True In the case of TrueTo operate the vehicle 112 and / or traction battery 124. The operations performed by the BECM 125 may include various examples. When the vehicle 112 is driven, the BECM 125 may use the real capacity Q True To adjust the discharge of the traction battery 124. For example, in response to determining the actual capacity Q since the last estimation True has decreased, the BECM 125 may provide a shorter range estimate and reduce the maximum discharge power of the traction battery 124 to save energy. Alternatively, the BECM 125 may calculate the actual capacity Q based on the actual capacity Q. True To adjust the charging operation. As an example, in response to determining the real capacity Q True Having decreased, the BECM 125 may reduce the power and / or total amount of battery charging via the EVSE 138 and / or regenerative charging.

[0043] The algorithm, method or process disclosed herein may be capable of being transported to or implemented by a computer, controller or processing device, which may include any dedicated electronic control unit or programmable electronic control unit. Similarly, the algorithm, method or process may be stored in various forms as data and instructions that can be executed by a computer or controller, including but not limited to information permanently stored on a non-writable storage medium such as a read-only memory device and information that can be modified and stored on a writable storage medium such as an optical disc, random access memory device or other magnetic and optical media. The algorithm, method or process may also be implemented as a software executable object. Alternatively, suitable hardware components may be used, such as an application specific integrated circuit, a field programmable gate array, a state machine or other hardware components or devices, or a combination of firmware, hardware and software components to implement the algorithm, method or process in whole or in part.

[0044] While exemplary embodiments have been described above, these embodiments are not intended to describe all possible forms encompassed by the claims. The words used in the specification are words of description rather than limitation, and it should be understood that various changes can be made without departing from the spirit and scope of the present disclosure. The terms "a processor" and "processors" are used interchangeably herein, as are the terms "a controller" and "controllers."

[0045] As previously mentioned, features of the various embodiments may be combined to form additional embodiments of the invention that may not be explicitly described or shown. Although various embodiments may have been described as providing advantages or being preferred over other embodiments or prior art implementations with respect to one or more desired characteristics, it will be recognized by those of ordinary skill in the art that one or more features or characteristics may be compromised to achieve desired overall system properties, depending on the specific application and implementation. These properties may include, but are not limited to, strength, durability, marketability, appearance, packaging, size, serviceability, weight, manufacturability, ease of assembly, etc. Therefore, embodiments described as being less desirable than other embodiments or prior art implementations with respect to one or more characteristics are not outside the scope of this disclosure and may be desirable for specific applications.

[0046] According to the present invention, a vehicle is provided having: a traction battery; an electric motor; a switch configured to electrically connect the traction battery and the electric motor; and a controller programmed to modify a maximum discharge power of the traction battery based on an estimated capacity of the traction battery, the estimated capacity being dependent on a set of previous instantaneous capacity values ​​of the traction battery and a current instantaneous capacity value of the traction battery, such that a sum of the previous instantaneous capacity values ​​and the current instantaneous capacity value is dependent on a state of charge of the traction battery when the switch is closed.

[0047] According to an embodiment, the total number further depends on the state of charge of the traction battery when the switch is closed at the first time instance and the second time instance.

[0048] According to an embodiment, the total number also depends on the charge experienced by the traction battery during a duration starting from the first time instance and ending at the second time instance.

[0049] According to an embodiment, the total number also depends on the current instantaneous capacity value.

[0050] According to an embodiment, the current instantaneous capacity value depends on the state of charge of the traction battery when the switch is closed at the first time instance and the second time instance.

[0051] According to an embodiment, the current instantaneous capacity value further depends on the charge experienced by the traction battery during a duration starting from the first time instance and ending at the second time instance.

[0052] According to an embodiment, the estimated capacity is an average of a previous instantaneous capacity value and a current instantaneous capacity value.

[0053] According to an embodiment, the set is a time series set.

[0054] According to the present invention, a method comprises modifying a maximum discharge power of a traction battery according to an estimated capacity of the traction battery, the estimated capacity being dependent on a set of previous instantaneous capacity values, the size of the set of previous instantaneous capacity values ​​being dependent on a state of charge of the traction battery at a first time instance and a second time instance.

[0055] In one aspect of the invention, the estimated capacity is also dependent on the current instantaneous capacity value.

[0056] In one aspect of the invention, the estimated capacity is an average of a previous instantaneous capacity value and a current instantaneous capacity value.

[0057] In one aspect of the invention, the magnitude is further dependent on the charge experienced by the traction battery during a duration starting from the first time instance and ending at the second time instance.

[0058] According to the present invention, a vehicle powertrain control system is provided having: a controller programmed to modify a maximum discharge power of a traction battery based on an estimated capacity of the traction battery, wherein the estimated capacity is dependent on a set of previous instantaneous capacity values ​​of the traction battery and a current instantaneous capacity value of the traction battery, and wherein a sum of the previous instantaneous capacity values ​​and the current instantaneous capacity value is dependent on a state of charge of the traction battery at a first time instance and a second time instance.

[0059] According to an embodiment, the total number also depends on the charge experienced by the traction battery during a duration starting from the first time instance and ending at the second time instance.

[0060] According to an embodiment, the total number also depends on the current instantaneous capacity value.

[0061] According to an embodiment, the current instantaneous capacity value depends on the state of charge of the traction battery at a first time instance and a second time instance.

[0062] According to an embodiment, the current instantaneous capacity value further depends on the charge experienced by the traction battery during a duration starting from the first time instance and ending at the second time instance.

[0063] According to an embodiment, the estimated capacity is an average of a previous instantaneous capacity value and a current instantaneous capacity value.

Claims

1. A vehicle comprising: traction batteries; Motor; a switch configured to electrically connect the traction battery and the motor; as well as a controller programmed to modify the maximum discharge power of the traction battery based on an estimated capacity of the traction battery, the estimated capacity being dependent on a set of previous instantaneous capacity values ​​of the traction battery and a current instantaneous capacity value of the traction battery, such that a sum of the previous instantaneous capacity values ​​and the current instantaneous capacity value is dependent on a state of charge of the traction battery when the switch is closed.

2. The vehicle of claim 1 , wherein the total is further dependent on the state of charge of the traction battery when the switch is closed at two moments in time.

3. The vehicle of claim 2, wherein the total is also dependent on the charge experienced by the traction battery during a duration beginning and ending at the two instants.

4. The vehicle of claim 3, wherein the total is further dependent on the current instantaneous capacity value.

5. The vehicle of claim 2, wherein the current instantaneous capacity value is dependent on the state of charge of the traction battery when the switch is closed at the two instances in time.

6. The vehicle of claim 5, wherein the current instantaneous capacity value is further dependent on the charge experienced by the traction battery during a duration beginning and ending at the two instants.

7. The vehicle of claim 1, wherein the estimated capacity is an average of the previous instantaneous capacity value and the current instantaneous capacity value. The vehicle of claim 1 , wherein the set is a time series set.

9. A method comprising: The maximum discharge power of the traction battery is modified according to an estimated capacity of the traction battery, the estimated capacity being dependent on a set of previous instantaneous capacity values, the size of the set of previous instantaneous capacity values ​​being dependent on the state of charge of the traction battery at two different moments in time.

10. The method of claim 9, wherein the estimated capacity is further dependent on a current instantaneous capacity value.

11. The method of claim 10, wherein the estimated capacity is an average of the previous instantaneous capacity value and the current instantaneous capacity value.

12. The method of claim 9, wherein said magnitude is further dependent upon said charge experienced by said traction battery over a duration beginning and ending at said two different times.

13. An automotive power control system, comprising: a controller programmed to modify a maximum discharge power of the traction battery based on an estimated capacity of the traction battery, wherein the estimated capacity is dependent on a set of previous instantaneous capacity values ​​of the traction battery and a current instantaneous capacity value of the traction battery, and wherein a sum of the previous instantaneous capacity values ​​and the current instantaneous capacity value is dependent on a state of charge of the traction battery at two different moments in time.

14. The automotive power control system of claim 13, wherein said total is further dependent upon the charge experienced by said traction battery during a duration beginning and ending at said two different times.

15. The automotive power control system of claim 13, wherein the total number is further dependent on the current instantaneous capacity value.

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