Energy management system for electric vehicles

Abstract

A monitoring computer is used in conjunction with an energy management system for an electric vehicle. The energy management system includes a battery system having multiple battery subsystems. One of the battery subsystems is an abnormal battery subsystem, while the remaining battery subsystems are normal battery subsystems. The monitoring computer includes at least one processor and at least one non-transitory computer-readable medium. The processor monitors the remaining state of charge, capacity, and resistance of the battery system, and monitors the remaining state of charge and capacity of the abnormal battery subsystem, calculates a lower bound value, calculates the remaining energy value of all the normal battery subsystems relative to the lower bound value, calculates the remaining energy value of the abnormal battery subsystem, and adds the remaining energy values ​​of the normal battery subsystems and the abnormal battery subsystem to determine the total remaining energy value of the battery system.

Description

Technical Field

[0001] This disclosure relates to a vehicle electrical system, and more specifically to an energy management system for an electric vehicle that determines the total remaining energy value of a battery system. Background Technology

[0002] In recent years, the use of electric motors to power electric vehicles has increased exponentially. To power these motors, battery packs consisting of numerous battery cells are used. Most battery cells can retain enough charge to power a vehicle for hundreds of miles. However, occasionally, a particular battery cell may have less charge than the others. Because this abnormal battery cell has less charge than the other normal cells, it continuously draws power from the normal battery subsystem, reducing the total remaining energy of the battery pack. Existing energy management systems assess the remaining energy of the battery pack, but lack a precise method to calculate the amount of power drawn by the abnormal battery cell. Instead, existing energy management systems calculate remaining energy based on the assumption that all battery cells are functioning correctly; or they only provide a rough estimate of the battery performance distribution. Therefore, the vehicle has less remaining energy (and remaining range) than the information conveyed to the driver. This can cause the electric vehicle to run out of power before reaching the driver's intended destination, leaving the driver stranded.

[0003] Therefore, while existing energy management systems have achieved their intended purpose, a completely new and improved energy management system is still needed to address these issues. Summary of the Invention

[0004] According to several aspects of this disclosure, a monitoring computer for an energy management system of an electric vehicle is provided. The energy management system includes a battery system configured to power the electric vehicle and includes a plurality of battery subsystems. One of the battery subsystems is further defined as an abnormal battery subsystem. The remaining battery subsystems are further defined as normal battery subsystems. The monitoring computer includes at least one processor and at least one non-transitory computer-readable medium including instructions, such that the processor is programmed to monitor the remaining state of charge, capacity, and resistance of the battery system, and to monitor the remaining state of charge and capacity of the abnormal battery subsystem. The processor is further programmed to calculate an integrated lower boundary value based on the remaining state of charge and capacity of the battery system and the remaining state of charge and capacity of the abnormal battery subsystem. The processor is further programmed to calculate the remaining energy values ​​of all the normal battery subsystems relative to the integrated lower boundary value, calculate the remaining energy values ​​of the abnormal battery subsystems, and add the remaining energy values ​​of the normal battery subsystems and the abnormal battery subsystems to determine the total remaining energy value of the battery system.

[0005] In one aspect, the processor is further programmed to calculate the actual energy consumption rate value of the electric vehicle based on at least one vehicle consumption rate variable, and to calculate the remaining range value based on the total remaining energy value and the actual energy consumption rate value.

[0006] In another aspect, the processor is further programmed to communicate with a global navigation satellite system (GNSS) network to determine the location and destination of the electric vehicle, calculate a travel distance value based on the route between the electric vehicle's location and the destination, compare the remaining travel range value with the travel distance value, and determine whether the electric vehicle can reach the destination.

[0007] In another aspect, the processor is further programmed to calculate a maximum energy consumption rate value based on the travel distance value, and to adjust the vehicle energy consumption rate variable if the remaining travel range value is less than the travel distance value, thereby reducing the actual energy consumption rate value to less than or equal to the maximum energy consumption rate value.

[0008] In another aspect, the processor is programmed to calculate the integrated lower boundary value based on the remaining state of charge and capacity of the battery system and based on the remaining state of charge and capacity of the abnormal battery subsystem, where a is the integrated lower boundary value; wherein SOC rem It is the remaining state of charge of the battery system; where Cap is the capacity of the battery system; and SOC is the remaining state of charge of the battery system. ab1-rem It is the remaining state of charge of the abnormal battery subsystem; and Cap ab1 It is the capacity of the abnormal battery subsystem.

[0009] In another aspect, the processor is programmed to calculate the remaining energy value of all the normal battery subsystems relative to the integrated lower boundary value, further defined as the processor being programmed to calculate the remaining energy value of all the normal battery subsystems according to the following formula:

[0010]

[0011] Where ΔE norm It is the remaining energy value of all the said normal battery subsystems, where n normal This represents the number of normal battery subsystems, where V oc It is the open-circuit voltage of one of the normal battery subsystems, and where V polar It is based on the resistance of one of the normal battery subsystems, and the polarity voltage of one of the normal battery subsystems.

[0012] In another aspect, the processor is programmed to calculate the remaining energy value of the malfunctioning battery subsystem, further specified as being programmed to calculate the remaining energy value of the malfunctioning battery subsystem according to the following formula:

[0013]

[0014] Where ΔE ab It is the remaining energy value of the abnormal battery subsystem.

[0015] According to several aspects of this disclosure, an energy management system for an electric vehicle is provided. The energy management system includes a battery system configured to power an electric vehicle and including multiple battery subsystems, one of which is further defined as an abnormal battery subsystem, and the remaining battery subsystems are further defined as normal battery subsystems. The energy management system also includes a monitoring computer, the monitoring computer including at least one processor and at least one non-transitory computer-readable medium. The at least one non-transitory computer-readable medium includes instructions that cause the processor to be programmed to monitor the remaining state of charge, capacity, and resistance of the battery system and to monitor the remaining state of charge and capacity of the abnormal battery subsystems. The processor is further programmed to calculate an integrated lower boundary value based on the remaining state of charge and capacity of the battery system and the remaining state of charge and capacity of the abnormal battery subsystems. The processor is further programmed to calculate the remaining energy values ​​of all the normal battery subsystems relative to the integrated lower boundary value, calculate the remaining energy values ​​of the abnormal battery subsystems, and add the remaining energy values ​​of the normal battery subsystems and the abnormal battery subsystems to determine the total remaining energy value of the battery system.

[0016] In one aspect, the processor of the monitoring computer is further programmed to calculate the actual energy consumption rate value of the electric vehicle based on at least one vehicle consumption rate variable, and to calculate the remaining range value based on the total remaining energy value and the actual energy consumption rate value.

[0017] In another aspect, the processor of the monitoring computer is further programmed to communicate with a Global Navigation Satellite System (GNSS) network to determine the location and destination of the electric vehicle, calculate a travel distance value based on the route between the location of the electric vehicle and the destination, compare the remaining travel range value with the travel distance value, and determine whether the electric vehicle can reach the destination.

[0018] In another aspect, the energy management system also includes a navigation interface configured to provide navigation instructions to the driver of the electric vehicle, wherein the processor of the monitoring computer is further programmed to construct navigation instructions based on the route between the location of the electric vehicle and the destination, and to transmit the navigation instructions to the navigation interface for communication with the driver.

[0019] According to several aspects of this disclosure, a method is provided for operating a monitoring computer for an energy management system of an electric vehicle. The energy management system includes a battery system. The battery system is configured to power an electric vehicle and includes multiple battery subsystems, one of which is further defined as an abnormal battery subsystem, and the remaining battery subsystems are further defined as normal battery subsystems. The monitoring computer includes at least one processor and at least one non-transitory computer-readable medium. The method includes monitoring the remaining state of charge, capacity, and resistance of the battery system, and monitoring the remaining state of charge and capacity of the abnormal battery subsystems. The method further includes calculating a lower bound value based on the remaining state of charge and capacity of the battery system and the remaining state of charge and capacity of the abnormal battery subsystems. The method further includes calculating the remaining energy values ​​of all the normal battery subsystems relative to the lower bound value, calculating the remaining energy values ​​of the abnormal battery subsystems, and adding the remaining energy values ​​of the normal battery subsystems and the abnormal battery subsystems to determine the total remaining energy value of the battery system.

[0020] In one aspect, the method further includes calculating the actual energy consumption rate value of the electric vehicle based on at least one vehicle consumption rate variable, and calculating the remaining range value based on the total remaining energy value and the actual energy consumption rate value.

[0021] In another aspect, the method also includes communicating with a Global Navigation Satellite System (GNSS) network to determine the location and destination of the electric vehicle, calculating a travel distance value based on the route between the location of the electric vehicle and the destination, comparing the remaining travel range value with the travel distance value, and determining whether the electric vehicle can reach the destination.

[0022] In another aspect, the method further includes calculating a maximum energy consumption rate value based on the travel distance value, and adjusting the vehicle consumption rate variable if the remaining travel range value is less than the travel distance value, thereby reducing the actual energy consumption rate value to less than or equal to the maximum energy consumption rate value.

[0023] In another aspect, the vehicle consumption rate variable is the speed of the electric vehicle, and if the remaining range value is less than the travel distance value, the vehicle consumption rate variable is adjusted to further limit the speed of the electric vehicle, thereby reducing the actual energy consumption rate value to less than or equal to the maximum energy consumption rate value.

[0024] In another aspect, the energy management system also includes a navigation interface configured to provide navigation instructions to the driver of the electric vehicle, wherein the processor of the monitoring computer is further programmed to construct navigation instructions based on the route between the location of the electric vehicle and the destination, and to transmit the navigation instructions to the navigation interface for communication with the driver.

[0025] In another aspect, the integration lower boundary value is calculated based on the remaining state of charge and capacity of the battery system and the remaining state of charge and capacity of the abnormal battery subsystem, where a is the integration lower boundary value, and SOC... rem It is the remaining state of charge of the battery system, where Cap is the capacity of the battery system, and SOC is... ab1-rem It is the remaining state of charge of the abnormal battery subsystem, and Cap ab1 It is the capacity of the abnormal battery subsystem.

[0026] In another aspect, calculating the remaining energy value of all said normal battery subsystems relative to the integrated lower boundary value is further defined as calculating the remaining energy value of all said normal battery subsystems according to the following formula:

[0027]

[0028] Where ΔE norm It is the remaining energy value of all the said normal battery subsystems, where n normal This represents the number of normal battery subsystems, where V oc It is the open-circuit voltage of one of the normal battery subsystems, and where V polar It is based on the resistance of one of the normal battery subsystems, and the polarity voltage of one of the normal battery subsystems.

[0029] In another aspect, calculating the remaining energy value of the abnormal battery subsystem is further defined as calculating the remaining energy value of the abnormal battery subsystem according to the following formula:

[0030]

[0031] Where ΔE ab It is the remaining energy value of the abnormal battery subsystem.

[0032] Based on the description herein, many more application areas will become apparent. It should be understood that the specifications and specific examples are intended for illustrative purposes only and are not intended to limit the scope of this disclosure. Attached Figure Description

[0033] The accompanying drawings described herein are for illustrative purposes only and are not intended to limit the scope of this disclosure in any way.

[0034] Figure 1 This is a schematic diagram of an example of an electric vehicle with an energy management system, wherein the energy management system has a monitoring computer that communicates with a battery system that includes an abnormal battery subsystem and multiple normal battery subsystems.

[0035] Figure 2 It is a graph showing the change in voltage as the state of charge of the battery system changes, and showing the remaining energy value of the abnormal battery subsystem and the remaining energy value of one of the normal battery subsystems.

[0036] Figure 3 It is a schematic diagram of a map showing the location of the electric vehicle, the destination of the electric vehicle, and the route between them.

[0037] Figure 4 This is a flowchart illustrating a method for operating the monitoring computer of the energy management system. Detailed Implementation

[0038] The following description is merely exemplary in nature and is not intended to limit this disclosure, application, or use.

[0039] Based on several aspects of this disclosure, and referring to Figure 1The diagram generally illustrates an energy management system 20 for an electric vehicle 22. The energy management system 20 includes a battery system 24 configured to power the electric vehicle and comprises multiple battery subsystems 26, wherein one of the battery subsystems 26 is further defined as an abnormal battery subsystem 26A, and the remaining battery subsystems 26 are further defined as normal battery subsystems 26B. The abnormal battery subsystem 26A retains a lower charge than each normal battery subsystem 26B. Under optimal conditions, all of the battery subsystems 26 are defined as normal battery subsystems 26B. However, different conditions may cause a battery subsystem 26 to be defined as the abnormal battery subsystem 26A. In one example, the abnormal battery subsystem 26A is a battery subsystem 26 that has reached the end of its service life and cannot retain a similar charge as the normal battery subsystem 26B, commonly referred to as a droop cell. In another example, the "abnormal" battery subsystem 26A is chemically different from the normal battery subsystem 26B and cannot maintain a similar charge or voltage as the normal battery subsystem 26B. This mixed chemical condition may occur due to variations in the battery subsystem 26 during production, such as changes in material availability and quality control data (e.g., different electrolytes, electrodes, charge generation, etc.). This mixed chemical condition may occur during the initial assembly of the battery system 24 or during maintenance of the battery system 24 (e.g., replacement of battery subsystem 26).

[0040] The battery subsystem 26 is a component that can collectively form the battery system 24. Typically, one or more battery packs supply power to the electric vehicle 22. Each battery pack may include one or more battery modules. Each battery module may include one or more battery cells. Thus, in one example, the battery subsystem 26 is a battery pack having a collection of battery packs forming the battery system 24. In another example, the battery subsystem 26 is the battery module, wherein a single battery pack containing the battery module defines the battery system 24. In yet another example, the battery subsystem 26 is the battery cell, wherein a single battery module containing the battery cell defines the battery system 24. However, the battery subsystem 26 can be any combination of components that can collectively form the battery system 24.

[0041] Because the abnormal battery subsystem 26A can retain a lower charge than the normal battery subsystem 26B, it continuously draws power from the normal battery subsystem 26B, reducing the total remaining energy of the battery system 24. Therefore, when an abnormal battery subsystem is present, the prediction of the total remaining energy of any battery system needs to consider the impact of the abnormal battery subsystem on the battery system. To this end, the energy management system 20 also includes a monitoring computer 28, which includes at least one processor 30 and at least one non-transitory computer-readable medium 32. The at least one non-transitory computer-readable medium 32 includes instructions that cause the processor 30 to be programmed to monitor the remaining state of charge, capacity, and resistance of the battery system 24, and to monitor the remaining state of charge and capacity of the abnormal battery subsystem 26A. The processor 30 is further programmed to calculate an integrated lower boundary value based on the remaining state of charge and capacity of the battery system 24 and based on the remaining state of charge and capacity of the abnormal battery subsystem 26A. The processor 30 is further programmed to calculate the remaining energy values ​​of all the normal battery subsystems 26B relative to the integrated lower boundary value, calculate the remaining energy value of the abnormal battery subsystem 26A, and add the remaining energy values ​​of the normal battery subsystems 26B and the abnormal battery subsystems 26A to determine the total remaining energy value of the battery system 24.

[0042] The battery system 24 may include an electronic chip 34 that communicates electronically with the monitoring computer 28 and is configured to detect the remaining state of charge, capacity, and resistance of the battery system 24. Similarly, each battery subsystem 26 may include an electronic chip 36 that communicates electronically with the monitoring computer 28 and is configured to detect the remaining state of charge and capacity of the battery system 24. The monitoring computer 28 may receive signals from the electronic chips 34 and 36 indicating the detected remaining state of charge, capacity, and resistance, and monitors the battery system 24 and the battery subsystem 26 accordingly. An example of monitoring the remaining state of charge, capacity, and resistance of a battery system and / or battery subsystem is shown in U.S. Patent Application No. 16 / 743,839, filed January 15, 2020, entitled “METHODAND SYSTEM FOR BATTERY CAPACITY ESTIMATION,” the disclosure of which is incorporated herein by reference.

[0043] Generally, the monitoring computer 28 calculates the remaining energy in each battery subsystem 26 and adds these values ​​to determine the total remaining energy value of the battery system 24. The amount of electricity drawn by the abnormal battery subsystem 26A from the normal battery subsystem 26B is reflected in the remaining energy calculation of the normal battery subsystem 26B through the integrated lower boundary value. The processor 30 is programmed to calculate the integrated lower boundary value based on the remaining state of charge and capacity of the battery system 24 and based on the remaining state of charge and capacity of the abnormal battery subsystem 26A. Where 'a' is the integrated lower boundary value, and SOC... rem It is the remaining state of charge of the battery system 24, where Cap is the capacity of the battery system 24, and SOC is the remaining state of charge. ab1-rem It is the remaining state of charge of the abnormal battery subsystem 26A, where Cap ab1 This refers to the capacity of the abnormal battery subsystem 26A. The processor is programmed to calculate the remaining energy value of all the normal battery subsystems 26B relative to the integrated lower boundary value. This can be further defined as calculating the remaining energy value of all the normal battery subsystems 26B according to the following formula:

[0044]

[0045] Where ΔE norm It is the remaining energy value of all the normal battery subsystems 26B, where n normal This is the number of 26B in a normal battery subsystem, where V oc It is the open-circuit voltage of one of the normal battery subsystems 26B, where V polar This is based on the resistance of one of the normal battery subsystems 26B and the polarity voltage of one of the normal battery subsystems 26B. The processor 30 is programmed to calculate the remaining energy value of the abnormal battery subsystem 26A, which is further defined as calculating the remaining energy value of the abnormal battery subsystem 26A according to the following formula:

[0046]

[0047] Where ΔE ab1 It is the remaining energy value of the abnormal battery subsystem 26A.

[0048] Figure 2 This is a graphical representation of the above calculation. More specifically, Figure 2 A graph showing the relationship between the open-circuit voltage (y-axis) and the state of charge (x-axis) is presented. The remaining state of charge (SOC) of battery system 24 is also shown. rem The figure shows the location marked 38 on the attached diagram. The remaining state of charge (SOC) of the abnormal battery subsystem 26A is indicated by this. ab1-remThe figure 40 indicates the location on the line. The integrated lower boundary value (a) is indicated at the location on the line. The figure 44 indicates the remaining state of charge (SOC) of one of the integrated lower boundary value (a) and the normal battery subsystem 26B. rem The offline region between ( ) represents the remaining energy value (i.e., ΔE) of each of the said normal battery subsystems 26B. norm Divide by n normal Figure 46 shows the remaining state of charge (SOC) of the abnormal battery subsystem 26A at zero and... ab1-rem The area between the lines 46 and 47. The area between the lines 46 and 47 represents the remaining energy value (ΔE) of the abnormal battery subsystem 26A. ab1 ).

[0049] In the battery system 24, there may be more than one abnormal battery subsystem 26A. The same general calculations described above can be used to assess the total remaining energy value of the battery subsystems 26. More specifically, the processor 30 is programmed to calculate the remaining energy value (i.e., ΔE as shown above) of all the normal battery subsystems 26B. norm In this calculation, the integrated lower boundary value (a) corresponds to the weakest anomalous battery subsystem 26A (i.e., the anomalous battery subsystem 26A with the worst charge retention capacity). The processor 30 is programmed to calculate the remaining energy value of the weakest anomalous battery subsystem 26A, which corresponds to ΔE as shown above. ab1 The processor is further programmed to calculate the remaining energy value of each of the remaining aberrant battery subsystems 26A. More specifically, the remaining energy value of each of the remaining aberrant battery subsystems is calculated individually. The remaining energy value is calculated starting from an integrated lower boundary value (x), which is a function of the state of charge and capacity of the weakest aberrant battery subsystem 26A and the specific aberrant battery subsystem 26A. Wherein, SOC abx-rem It is the remaining state of charge of any of the other abnormal battery subsystems 26A, and Cap abx This refers to the capacity of the specific abnormal battery subsystem 26A. The remaining energy value of the specific abnormal battery subsystem 26A is calculated according to the following formula:

[0050]

[0051] Where ΔE abx This is the remaining energy value of the specific anomalous battery subsystem 26A. Except for the weakest anomalous battery subsystem 26A, the integrated lower boundary value (x) and remaining energy value ΔE of each anomalous battery subsystem 26A are calculated. abxThe processor 30 is programmed to store the remaining energy values ​​(ΔE) of all the normal battery subsystems 26B. norm The remaining energy value (ΔE) of the weakest abnormal battery subsystem 26A ab1 ), and the remaining energy value (ΔE) of each of the other abnormal battery subsystems 26A. abx The values ​​are added together to determine the total remaining energy value of the battery system 24.

[0052] As described above, the battery subsystem 26 can be configured as one or more battery packs. In one example, the battery subsystem 26 includes two battery packs configured to alternate between series and parallel connections. Therefore, the polarity voltage and open-circuit voltage of the battery packs are combined in series and separated in parallel. Thus, the total residual energy value lies between the series and parallel connections. More specifically, the total residual energy value (ΔE) of the series-connected battery packs... series The total remaining energy of the parallel battery pack is equal to the sum of the remaining energy values ​​of the battery packs. parallel The total remaining energy value (ΔE) is equal to the sum of the remaining energy values ​​of the battery packs multiplied by the self-balancing efficiency, which characterizes the loss caused by self-charging to balance in the parallel battery packs. Depending on the needs of the electric vehicle 22, the battery packs switch between parallel and series configurations. Therefore, the processor 30 is programmed to calculate the adjusted total remaining energy value (ΔE) based on an example of two parallel battery packs. adj-glob ):

[0053] ΔE adj-glob =η(ΔEp1+ΔEp2)

[0054] Wherein, ΔEp1 is the remaining energy value of one of the battery packs, ΔEp2 is the remaining energy value of the other battery pack, and η is the self-balancing efficiency. The self-balancing efficiency is approximately 0.98 to 0.995, depending on the thermal resistance loss of the battery pack and the imbalance between the battery packs.

[0055] The processor 30 is programmed to calculate the actual energy consumption rate value of the electric vehicle 22 based on at least one vehicle consumption rate variable; and to calculate the remaining range value based on the total remaining energy consumption value and the actual energy consumption rate value. In one example, the vehicle consumption rate variable is the speed of the electric vehicle 22. The faster the speed, the higher the actual energy consumption rate value of the electric vehicle 22, because the electric vehicle 22 requires more energy to drive. The higher the actual energy consumption rate value, the lower the remaining range value.

[0056] The processor 30 is further programmed to work with a Global Navigation Satellite System (GNSS) network 48 (such as...). Figure 1(As shown) to communicate to determine the location 50 and destination 52 of the electric vehicle 22, and to calculate the travel distance value of the route 54 between the location 50 and destination 52 of the electric vehicle 22 (e.g., Figure 3 As shown in the diagram, the remaining travel distance is compared with the travel distance to determine whether the electric vehicle 22 can reach the destination 52. More specifically, the electric vehicle 22 may include an antenna 56 for wireless communication with the GNSS network 48, such as... Figure 1 As shown. The antenna 56 communicates electronically with the monitoring computer 28. The processor 30 can communicate with the GNSS network 48 to determine the position 50 of the electric vehicle 22 in real time. The processor 30 can also communicate with the GNSS network 48 to spatially locate the destination 52 relative to the position 50 of the electric vehicle 22. Based on a pre-programmed travel route stored in the at least one non-transitory computer-readable medium 32, a route 54 can be determined between the position 50 of the electric vehicle 22 and the destination 52 on the travel route. According to the route 54, the travel distance between the position 50 of the electric vehicle 22 and the destination 52 can be calculated. Both the remaining travel range value and the travel distance value are units of measurement. Therefore, the remaining travel range value and the travel distance value can be compared to determine whether the electric vehicle 22 can reach the destination 52. If the remaining travel range value is greater than or equal to the travel distance value, the electric vehicle 22 can reach the destination 52.

[0057] The processor 30 is further programmed to calculate a maximum energy consumption rate value based on the travel distance value, and if the remaining travel range value is less than the travel distance value, to adjust the vehicle energy consumption rate variable to reduce the actual energy consumption rate value to less than or equal to the maximum energy consumption rate. More specifically, the maximum energy consumption rate value is directly related to the travel distance value and traffic flow on the route. Therefore, adjusting the vehicle energy consumption rate variable can increase or decrease the actual energy consumption rate. As mentioned above, the vehicle energy consumption rate variable can be the speed of the electric vehicle 22; however, any suitable vehicle energy consumption rate variable can be adjusted. The processor 30 is programmed to adjust the vehicle energy consumption rate variable, which can be further defined as reducing the speed of the electric vehicle 22 if the remaining travel range value is less than the travel distance value, to reduce the actual energy consumption rate value to less than or equal to the maximum energy consumption rate value. In the example shown in the figure, the electric vehicle 22 includes at least one electric motor 58 configured to drive the electric vehicle 22. The processor 30 can restrict the commutation of the electric motor 58 to prevent the electric vehicle 22 from traveling at speeds exceeding which could cause the actual energy consumption rate value to be greater than the maximum energy consumption rate value.

[0058] In one example, the destination 52 is further defined as a vehicle service center suitable for servicing the malfunctioning battery subsystem 26A. More specifically, the processor 30 may communicate with the GNSS network 48 to determine the locations 50 of one or more vehicle service centers near the location 50 of the electric vehicle 22, determine a route 54 to each vehicle service center, calculate the driving distance value between the location 50 of the electric vehicle 22 and each of the vehicle service centers, and determine the best reachable vehicle service center based on the remaining range value and the driving distance value of the vehicle service station. However, the destination 52 may be a charging station or the electric vehicle driver's residence, an emergency location (e.g., a police station), or any other suitable location from which the electric vehicle driver may obtain new power or service for the malfunctioning subsystem 26A.

[0059] The energy management system 20 may also include, for example: Figure 1The navigation interface 60 is shown. The navigation interface 60 is configured to provide navigation instructions to the driver of the electric vehicle 22. Non-limiting examples of the navigation interface 60 include an interactive map on a visual display, visual turn-by-step instructions projected onto a head-up display (HUD) on the windshield of the vehicle 22, and auditory turn-by-step instructions spoken through the speakers of the vehicle 22. The processor 30 is further programmed to construct navigation instructions based on a route 54 between the electric vehicle 22's location 50 and its destination 52, and to transmit these instructions to the navigation interface 60 to be communicated to the driver.

[0060] The energy management system 20 can perform various automatic controls based on any of the aforementioned values, including (but not limited to) the total remaining energy value, the actual energy consumption rate value, the remaining range value, the driving distance value, and the maximum energy consumption rate value. For example, the energy management system 20 automatically changes the performance mode of the electric vehicle 22, which controls performance characteristics such as acceleration, maximum speed, and braking. The energy management system 20 can also dynamically change the route 54 of the electric vehicle 22 to ensure that the electric vehicle reaches the destination 52. Furthermore, the energy management system 20 can change the cruise control mode or speed to efficiently manage the total remaining energy value of the battery system 24.

[0061] The present invention also discloses a method 200 for operating a monitoring computer 28 for an energy management system 20 of the electric vehicle 22, such as... Figure 4 As shown in the diagram. The method includes monitoring the remaining state of charge, capacity, and resistance of the battery system 24 (as shown in box 202), and monitoring the remaining state of charge and capacity of the abnormal battery subsystem 26A (as shown in box 204). The method also includes calculating a lower bound value for integration based on the remaining state of charge and capacity of the battery system 24 and the abnormal battery subsystem 26A (as shown in box 206). The method further includes calculating the remaining energy values ​​of all normal battery subsystems 26B relative to the lower bound value for integration (as shown in box 208), calculating the remaining energy value of the abnormal battery subsystem 26A (as shown in box 210), and adding the remaining energy values ​​of the normal battery subsystems 26B and the abnormal battery subsystem 26A to determine the total remaining energy value of the battery system 24 (as shown in box 212).

[0062] The method further includes calculating the actual energy consumption rate value of the electric vehicle 22 based on at least one vehicle consumption rate variable (as shown in box 214), and calculating the remaining travel range value based on the total remaining energy value and the actual energy consumption rate value (as shown in box 216). The method also includes communicating with the GNSS network 48 to determine the position 50 and destination 52 of the electric vehicle 22 (as shown in box 218), calculating the travel distance value based on the route 54 between the position 50 and destination 52 of the electric vehicle 22 (as shown in box 220), comparing the remaining travel range value with the travel distance value (as shown in box 222), and determining whether the electric vehicle 22 can reach the destination 52 (as shown in box 224).

[0063] If the electric vehicle 22 can reach the destination 52, then the vehicle 22 continues to drive towards the destination 52 (as shown in box 226). If the electric vehicle 22 cannot reach the destination 52, the method may further include calculating a maximum energy consumption rate value based on the travel distance value (as shown in box 228), and if the remaining travel range value is less than the travel distance value, adjusting the vehicle consumption rate value to reduce the actual energy consumption value to less than or equal to the maximum energy consumption rate value (as shown in box 230). As mentioned above, the vehicle consumption rate variable may be the speed of the electric vehicle 22. Therefore, adjusting the vehicle consumption rate variable (as shown in box 230) may be further defined as reducing the speed of the electric vehicle 22 if the remaining travel range value is less than the travel distance value, to reduce the actual energy consumption rate value to less than or equal to the maximum energy consumption rate value. As mentioned above, the energy management system 20 may also include a navigation interface 60 configured to provide navigation instructions to the driver of the electric vehicle 22. The method further includes constructing the navigation instructions based on the route 54 between the electric vehicle's location 50 and destination 52, and transmitting the navigation instructions to the navigation interface 60 to convey them to the driver (as shown in box 232).

[0064] As shown in box 206, the integrated lower boundary value is further defined based on the remaining state of charge and capacity of the battery system 24 and the remaining state of charge and capacity of the abnormal battery subsystem 26A, where a is the integrated lower boundary value, and SOC is... rem It is the remaining state of charge of the battery system 24, where Cap is the capacity of the battery system 24, and SOC is the remaining state of charge. ab1-rem It is the remaining state of charge of the abnormal battery subsystem 26A, and where Cap ab1This refers to the capacity of the abnormal battery subsystem 26A. Furthermore, as shown in box 208, calculating the remaining energy value of all the normal battery subsystems 26B relative to the integrated lower boundary value is further defined as calculating the remaining energy value of all the normal battery subsystems 26B according to the following formula:

[0065]

[0066] Where ΔE norm It is the remaining energy value of all the normal battery subsystems 26B, where n normal This is the number of 26B in a normal battery subsystem, where V oc It is the open-circuit voltage of one of the normal battery subsystems 26B, and V therein polar It is based on the resistance of one of the normal battery subsystems 26B, and the polarity voltage of one of the normal battery subsystems 26B.

[0067] As shown in box 210, the calculation of the remaining energy value of the abnormal battery subsystem 26A is further defined as follows: the remaining energy value of the abnormal battery subsystem 26A is calculated according to the following formula:

[0068]

[0069] Where ΔE ab It is the remaining energy value of the abnormal battery subsystem 26A.

[0070] Therefore, the monitoring computer 28, the energy management system 20, and the corresponding method 200 have several advantages. Calculating the remaining energy value of each battery subsystem 26 and summing these values ​​to generate a total remaining energy value indicates that the abnormal battery subsystem 26A is continuously drawing power from the normal battery subsystem 26B. Furthermore, considering the abnormal battery subsystem 26A to calculate the remaining range value and determine the destination 52 that the electric vehicle 22 can reach, it can be ensured that the driver will not be stranded during commuting. The aforementioned problems are specific to a particular technical field. The advantages described herein solve these problems.

[0071] The descriptions in this disclosure are merely exemplary in nature, and any changes made without departing from the general meaning of this disclosure will also fall within its scope. Such changes should not be considered as departing from the spirit and scope of this disclosure.

Claims

1. A monitoring computer for an energy management system of an electric vehicle, the energy management system including a battery system configured to power the electric vehicle and including a plurality of battery subsystems, wherein one battery subsystem is further defined as an abnormal battery subsystem, and the remaining battery subsystems are further defined as normal battery subsystems, the monitoring computer comprising: At least one processor; and At least one non-transitory computer-readable medium including instructions, such that the processor is programmed to: Monitor the remaining state of charge, capacity, and resistance of the battery system; Monitor the remaining state of charge and capacity of the abnormal battery subsystem; Calculate the integrated lower boundary value based on the remaining state of charge and capacity of the battery system and the remaining state of charge and capacity of the abnormal battery subsystem; Calculate the remaining energy values ​​of all the normal battery subsystems relative to the integrated lower boundary value; Calculate the remaining energy value of the abnormal battery subsystem; as well as The remaining energy values ​​of the normal battery subsystem and the abnormal battery subsystem are added together to determine the total remaining energy value of the battery system.

2. The monitoring computer according to claim 1, wherein the processor is further programmed to: Calculate the actual energy consumption rate value of the electric vehicle based on at least one vehicle consumption rate variable; and The remaining travel range is calculated based on the total remaining energy value and the actual energy consumption rate value.

3. The monitoring computer according to claim 2, wherein the processor is further programmed to: Communicate with a Global Navigation Satellite System (GNSS) network to determine the location and destination of the electric vehicle; Calculate the travel distance based on the route between the location of the electric vehicle and the destination; Compare the remaining travel range value with the travel distance value; as well as Determine whether the electric vehicle can reach its destination.

4. The monitoring computer according to claim 3, wherein the processor is further programmed to: Calculate the maximum energy consumption rate based on the travel distance value; and If the remaining travel range value is less than the travel distance value, the vehicle consumption rate variable is adjusted to reduce the actual energy consumption rate value to less than or equal to the maximum energy consumption rate value.

5. The monitoring computer of claim 1, wherein the processor is programmed to calculate the remaining energy value of all the normal battery subsystems relative to the integrated lower boundary value, further defined as the processor being programmed to calculate the remaining energy value of all the normal battery subsystems according to the following formula: Where a is the lower boundary value of the integration; SOC rem It is the remaining state of charge of the battery system; Where Cap is the capacity of the battery system; Where ∆ E norm This is the remaining energy value of all the aforementioned normal battery subsystems; in n normal This refers to the number of normal battery subsystems; in V oc It is the open-circuit voltage of one of the normal battery subsystems; and in V polar It is the polarity voltage of one of the normal battery subsystems based on the resistance of one of the normal battery subsystems.

6. The monitoring computer according to claim 1, wherein the processor is programmed to calculate the remaining energy value of the abnormal battery subsystem, further defined as the processor being programmed to calculate the remaining energy value of the abnormal battery subsystem according to the following formula: Where ∆ E ab It is the remaining energy value of the abnormal battery subsystem; SOC ab1_rem It is the remaining state of charge of the abnormal battery subsystem, and Cap ab1 It is the capacity of the abnormal battery subsystem; in V oc It is the open-circuit voltage of one of the normal battery subsystems; and in V polar It is the polarity voltage of one of the normal battery subsystems based on the resistance of one of the normal battery subsystems.

7. A method of operating a monitoring computer for an energy management system of an electric vehicle, the energy management system including a battery system configured to power the electric vehicle and including a plurality of battery subsystems, one of which is further defined as an abnormal battery subsystem and the remaining battery subsystems are further defined as normal battery subsystems, the monitoring computer including at least one processor and at least one non-transitory computer-readable medium, the method comprising: Monitor the remaining state of charge, capacity, and resistance of the battery system; Monitor the remaining state of charge and capacity of the abnormal battery subsystem; Calculate the integrated lower boundary value based on the remaining state of charge and capacity of the battery system and the remaining state of charge and capacity of the abnormal battery subsystem; Calculate the remaining energy values ​​of all the normal battery subsystems relative to the integrated lower boundary value; Calculate the remaining energy value of the abnormal battery subsystem; as well as The remaining energy values ​​of the normal battery subsystem and the abnormal battery subsystem are added together to determine the total remaining energy value of the battery system.

8. The method according to claim 7, further comprising: Calculate the actual energy consumption rate value of the electric vehicle based on at least one vehicle consumption rate variable. as well as The remaining travel range is calculated based on the total remaining energy value and the actual energy consumption rate value.

9. The method according to claim 8, further comprising: Communicating with a Global Navigation Satellite System (GNSS) network to determine the location and destination of the electric vehicle; Calculate the travel distance based on the route between the location of the electric vehicle and the destination; Compare the remaining travel range value with the travel distance value; as well as Determine whether the electric vehicle can reach its destination.

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