Method and system for controling electric vehicle charge

Abstract

An electric vehicle charging control method and a system using the same are provided. According to one embodiment of the present disclosure, the electric vehicle charging control method performed by a charging control system may include the step of receiving driving information of an electric vehicle, the step of monitoring the state of a battery equipped in the electric vehicle, the step of determining whether the electric vehicle can drive to a final destination, and the step of recommending a recommended charge amount of the battery in the electric vehicle using the received driving information and the monitored state of the battery when it is determined that driving is not possible.

Description

Technology Field

[0001] The present disclosure relates to a method for controlling the charging of an electric vehicle. More specifically, it relates to a method for recommending a charging amount that reflects state information of a battery in an electric vehicle. Background Technology

[0002] When charging electric vehicles, it is common practice to determine the charging amount by considering only the current charge (SoC) remaining in the vehicle's battery. Consequently, overcharging frequently occurs while ignoring variables related to the battery itself, in addition to the voltage stored in the battery.

[0003] Since electric vehicles have the characteristic of constantly flowing current, there is a risk that if a voltage exceeding the currently permissible level is applied to an aging battery, it can easily lead to secondary accidents such as fire.

[0004] In addition, continuously overcharging the battery can accelerate the aging of the battery, which may lead to a decrease in the driving range of the electric vehicle equipped with the battery. Conversely, charging too little or always charging a constant amount may consume unnecessary resources (e.g., increased estimated time of arrival) regardless of driving to the destination.

[0005] Therefore, when determining the charge amount of an electric vehicle, it is required to provide a method for recommending an appropriate charge amount that reflects the current state and performance of the battery through monitoring of the battery itself, and a system to which such a control method is applied. Prior art literature

[0006] Korean Published Patent No. 10-2020-0117721 (Published Oct. 14, 2020) Korean Registered Patent No. 10-2304745 (Registered Sep. 15, 2021) The problem to be solved

[0007] The technical problem to be solved in some embodiments of the present disclosure is to provide a method for monitoring the state and performance of a battery in an electric vehicle and a system to which the method is applied.

[0008] Another technical problem to be solved in some embodiments of the present disclosure is to provide a method for determining whether an electric vehicle can drive to a final destination based on driving information obtained from the electric vehicle and monitored battery status information, and a system to which the method is applied.

[0009] Another technical problem to be solved in some embodiments of the present disclosure is to provide a method for providing a recommended charge amount of a battery that enables driving to a final destination by reflecting the state of the battery in a monitored electric vehicle, and a system to which the method is applied.

[0010] The technical problems of the present invention are not limited to those mentioned above, and other unmentioned technical problems will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0011] An electric vehicle charging control method according to one embodiment of the present disclosure for solving the above technical problem may include the steps of receiving driving information of an electric vehicle, monitoring the state of a battery equipped in the electric vehicle, determining whether the electric vehicle can drive to a final destination, and, if it is determined that driving is not possible, recommending a recommended charge amount of the battery in the electric vehicle using the received driving information and the monitored state of the battery.

[0012] In one embodiment, the step of receiving driving information of the electric vehicle may include receiving at least one of charging scheduling data of the electric vehicle, driving pattern data of the electric vehicle, data regarding the final destination of the electric vehicle, and data detected by an external sensor of the electric vehicle.

[0013] In one embodiment, the step of monitoring the condition of the battery in the electric vehicle may include determining the degree of aging of the battery, the expected lifespan of the battery, the internal deviation of the battery, and the safety of the battery.

[0014] In one embodiment, the step of determining the degree of aging of the battery may include the step of determining the degree of reduction in the chargeable capacity of the battery using charging scheduling data of the electric vehicle.

[0015] In one embodiment, the step of determining the degree of aging of the battery may include the step of determining the degree of reduction in the chargeable capacity of the battery using data on temperature and shock detected by an external sensor of the electric vehicle.

[0016] In one embodiment, the step of determining the expected lifespan of the battery may include calculating the cycle in which the chargeable capacity of the battery decreases below the minimum reference SOC value of the battery by utilizing the rate of decrease in the chargeable capacity of the battery. Additionally, temperature data detected by the external sensor of the electric vehicle may be used to determine the expected lifespan of the battery. For example, if the number of times the battery is charged or the parking time is analyzed under very low external temperatures and a specific threshold is exceeded, a penalty may be applied to the expected lifespan (SoL) value of the battery and reflected in the recommended charge amount recommendation logic.

[0017] In one embodiment, the step of determining the internal deviation of the battery may include, when the battery is a battery pack composed of a plurality of cells, the step of calculating the difference in state indicators of individual cells within the battery pack.

[0018] In one embodiment, the step of determining the safety of the battery may include the step of classifying the safety status of the battery by grade. In this case, the safety status of the battery may be classified into any one of the grades of good, caution, and danger.

[0019] In one embodiment, the step of classifying the safety status of the battery by grade may include the step of outputting a warning message to the communication controller of the electric vehicle when the safety status of the battery is a caution grade.

[0020] In one embodiment, the step of classifying the safety status of the battery by grade may include a step of controlling the driving of the electric vehicle to be restricted when the safety status of the battery is a risk grade.

[0021] In one embodiment, the step of determining whether the electric vehicle can drive to a final destination may include the step of calculating the driving range of the electric vehicle using the monitored battery status and the step of determining whether the electric vehicle can drive to a final destination using the calculated driving range.

[0022] In one embodiment, the step of calculating the driving range of the electric vehicle using the monitored battery status may include the step of updating the battery status information equipped in the electric vehicle using the driving pattern of the electric vehicle and the step of calculating the driving range of the electric vehicle using the updated battery status information.

[0023] In one embodiment, when it is determined that the electric vehicle cannot drive to a final destination, the step of recommending a recommended charge amount for the battery in the electric vehicle using the received driving information and the monitored battery status may include the step of displaying the location of a passing charging station between the current location of the electric vehicle and the final destination of the electric vehicle.

[0024] In one embodiment, the method may further include the step of acquiring a machine learning model that has learned data on the state of the monitored battery and the step of determining a recommended charge amount for the battery in the electric vehicle using the learned machine learning model.

[0025] An electric vehicle charging control device according to another embodiment of the present disclosure for solving the above technical problem may include a data collection unit for receiving driving information of an electric vehicle, a monitoring unit for monitoring the state of a battery equipped in the electric vehicle, a judgment unit for determining whether the electric vehicle can drive to a final destination, and a control unit for recommending a recommended charging amount of the battery in the electric vehicle using the received driving information and the monitored state of the battery when it is determined that driving is not possible.

[0026] A charging control system implemented as a computing system according to another embodiment of the present disclosure for solving the above technical problem may include a network interface for receiving monitoring information regarding a battery provided in an electric vehicle, a memory for loading a charging amount recommendation program using the monitoring information regarding the battery provided in the electric vehicle, and one or more processors for executing the charging amount recommendation program. In this case, the charging amount recommendation program may include an instruction for receiving driving information of the electric vehicle, an instruction for monitoring the status of the battery provided in the electric vehicle, an instruction for determining whether driving to the final destination of the electric vehicle is possible, and, if driving is determined not to be possible, an instruction for recommending a recommended charging amount of the battery in the electric vehicle using the received driving information and the monitored battery status. Brief explanation of the drawing

[0027] FIG. 1 is a diagram illustrating an environment in which an electric vehicle charging control method according to one embodiment of the present disclosure can be applied. FIG. 2 is a drawing for explaining the configuration of an electric vehicle charging control device according to another embodiment of the present disclosure. FIG. 3 is a drawing for illustrating driving information of an electric vehicle received according to some embodiments of the present disclosure. FIG. 4 is a drawing for explaining state information of a battery provided in an electric vehicle that is monitored according to some embodiments of the present disclosure. FIG. 5 is a flowchart of an electric vehicle charging control method according to one embodiment of the present disclosure. FIGS. 6 to 9 are detailed flowcharts for explaining some operations of the electric vehicle charging control method described with reference to FIG. 5. FIG. 10 is a diagram illustrating a machine learning model that outputs a recommended charge amount based on battery status information input according to some embodiments of the present disclosure. FIGS. 11 and 12 are drawings for illustrating state information of a battery monitored according to some embodiments of the present disclosure. FIG. 13 is a drawing for illustrating a screen in which a recommended charging amount and a charging station are displayed according to some embodiments of the present disclosure. FIG. 14 is a hardware configuration diagram of a computing system that can be used as a component in some embodiments of the present disclosure. Specific details for implementing the invention

[0028] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the attached drawings. The advantages and features of the present invention and the methods for achieving them will become clear by referring to the embodiments described below in detail together with the attached drawings. However, the technical concept of the present invention is not limited to the following embodiments but can be implemented in various different forms. The following embodiments are provided merely to complete the technical concept of the present invention and to fully inform those skilled in the art of the scope of the present invention, and the technical concept of the present invention is defined only by the scope of the claims.

[0029] In describing the present disclosure, if it is determined that a detailed description of related known configurations or functions could obscure the essence of the invention, such detailed description is omitted.

[0030] Additionally, terms such as first, second, (a), (b), etc., may be used to describe the components of the present disclosure. These terms are intended only to distinguish the components from other components and do not limit the nature, order, or sequence of the components. Where it is stated that a component is "connected," "coupled," or "joined" to another component, it should be understood that the component may be directly connected or joined to the other component, but that another component may also be "connected," "coupled," or "joined" between each component.

[0031] As used in this disclosure, “comprises” and / or “comprising” do not exclude the presence or addition of one or more other components, steps, actions, and / or elements to the mentioned components, steps, actions, and / or elements.

[0032] Hereinafter, various embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0033] Before describing an electric vehicle charging control method according to one embodiment of the present disclosure, we intend to describe an environment in which some embodiments of the present disclosure may be applied with reference to FIG. 1.

[0034] Referring to FIG. 1, the charging control system (1000) can receive driving information (5) from the electric vehicle (1) through a network (3). Additionally, the charging control system (1000) can use the received driving information (5) to display the recommended charging amount (7) of the battery in the electric vehicle (1) on a user terminal (9) linked to the electric vehicle (1).

[0035] At this time, the charging control system (1000) can be understood as a subject implementing an electric vehicle charging control method according to one embodiment of the present disclosure, and can also be understood as an electric vehicle charging control device according to another embodiment of the present disclosure. A detailed explanation thereof will be provided later with reference to FIG. 2. However, for convenience of explanation, the present disclosure will describe the charging control system (1000) as a single subject combined with a computing device.

[0036] Returning to Fig. 1, the charging control system (1000) may include a process of calculating the capacity of the battery required for the electric vehicle (1) to drive to a set destination.

[0037] For example, according to some embodiments of the present disclosure, the charging control system (1000) can calculate the capacity of the battery required to drive to the set destination based on the distance to the final destination set by the electric vehicle (1), the history of the electric vehicle (1) being charged, etc.

[0038] In addition, the charging control system (1000) can calculate the required charging amount of the battery by implementing the charging control method of the present disclosure and using driving information (5) received from the electric vehicle (1) to further reflect the state of the battery equipped in the electric vehicle (1).

[0039] With conventional methods, the required charge amount can be calculated by considering only the current State of Charge (SoC) of the battery equipped in the electric vehicle. As a result, the reduced capacity of the battery due to continuous aging and degradation is not taken into account, and a voltage that the aged battery cannot handle is applied, which can cause a major accident.

[0040] On the other hand, according to the present disclosure, the charging control system (1000) can solve the problem by using driving information (5) to additionally reflect specific indicators regarding the current state and performance of the battery and providing an appropriate amount of charge according to the state of the battery.

[0041] Specifically, according to some embodiments of the present disclosure, the charging control system (1000) can calculate the chargeable capacity of an aged battery by reflecting specific indicators regarding the current state and performance of the battery, such as the degree of aging (SoH, State of Health), the expected lifespan (SoL, State of Life), the internal deviation (SoB, State of Balance), and the safety (SoS, State of Safety) of the battery.

[0042] Subsequently, the charging control system (1000) can display the calculated recommended charge amount of the battery on a user terminal (9) linked to the electric vehicle (1). That is, the charging control system (1000) can recommend to a driver who intends to charge the electric vehicle (1) a charge amount for driving to a destination, which is also a charge amount that is currently permissible in the battery of the electric vehicle.

[0043] Additionally, the charging control system (1000) can display a group of recommended charging stations on a user terminal (9) linked to the electric vehicle (1) according to the recommended charging amount of the battery calculated.

[0044] At this time, the user terminal (9) linked to the electric vehicle (1) on which the recommended charging amount or charging station candidate group is displayed may be implemented as a Center Information Display (CID), a Head-Up Display (HUD), a personal / vehicle terminal, and a display device capable of user input or pad operation. However, this may not be limited to the scope of the present disclosure.

[0045] Up to now, with reference to FIG. 1, an environment in which an electric vehicle charging control method can be applied according to one embodiment of the present disclosure has been described. Below, with reference to FIG. 2, a configuration of a device capable of implementing an electric vehicle charging control method as another embodiment of the present disclosure will be described.

[0046] FIG. 2 is a diagram illustrating the configuration of an electric vehicle charging control device according to another embodiment of the present disclosure. At this time, for the convenience of explaining the present disclosure, the charging control device of FIG. 2 is to be described as an object to which the electric vehicle charging control method according to one embodiment of the present disclosure is applied, and is to be treated in the same way as the charging control system described in FIG. 1.

[0047] Referring to FIG. 2, the charging control device (1000) may include a data collection unit (100) for acquiring driving information of an electric vehicle to be charged and a monitoring unit (200) for monitoring the state of a battery equipped in the electric vehicle.

[0048] Additionally, the charging control device (1000) may include a judgment unit (300) that determines whether the electric vehicle can drive to a preset final destination, and a control unit (40) that recommends a recommended charge amount for the battery using driving information and battery status information, etc., when it is determined that the electric vehicle cannot drive to the final destination with the current charge amount of the battery.

[0049] First, the driving information obtained by the data collection unit (100) of the charging control device (1000) can be, for example, at least one of the following: charging scheduling data of the electric vehicle, driving pattern data of the electric vehicle, data regarding the final destination of the electric vehicle, and data detected by the external sensor of the electric vehicle. A detailed explanation thereof will be provided later with reference to FIG. 3.

[0050] In one embodiment, the charging control device (1000) can analyze the driver's charging pattern and driving pattern to the same destination obtained by the data collection unit (100) and calculate and recommend the amount of charge to be charged to the battery according to the current battery status.

[0051] In addition, as an embodiment, the charging control device (1000) may calculate and recommend the amount of charge to be charged to the battery based on the condition of the battery due to external temperature or external shock obtained by the data collection unit (100).

[0052] In addition, the monitoring unit (200) of the charging control device (1000) can determine the state or performance of the battery, including the current charge amount (SoC) of the battery equipped in the electric vehicle, the degree of aging (SoH) of the battery, the expected lifespan (SoL) of the battery, the internal deviation (SoB) of the battery, and the safety level (SoS) of the battery. A detailed explanation thereof will be provided later with reference to FIG. 6.

[0053] In addition, at this time, the monitoring unit (200) of the charging control device (1000) may set different monitoring periods for each state indicator of the battery. For example, the monitoring unit (200) of the charging control device (1000) may monitor the safety level (SoS) and internal deviation (SoB) of the battery in real time, and may periodically monitor the degree of aging (SoH) of the battery and charging patterns based on the previously received charging history of the battery over a certain period. However, this may not be limited to the scope of the present disclosure.

[0054] In one embodiment, the charging control device (1000) may determine that the degree of aging (SoH) or safety (SoS) of the battery in the electric vehicle has reached a serious level according to the state of the battery determined by the monitoring unit (200). At this time, the charging control device (1000) may display a message restricting driving along with a warning message regarding the driving of the electric vehicle on the user terminal of the electric vehicle.

[0055] In addition, the judgment unit (300) of the charging control device (1000) can calculate the driving distance of the electric vehicle using the battery status information. Subsequently, the judgment unit (30) of the charging control device (1000) can determine whether the electric vehicle can drive to a pre-set destination based on the calculated driving distance. A detailed explanation of this will be provided later with reference to FIG. 8.

[0056] In one embodiment, the charging control device (1000) and the judgment unit (300) can use the battery status by updating it by reflecting the driver's driving pattern, etc., in the driving information received earlier in the process of calculating the driving range of the electric vehicle according to the monitoring result of the battery.

[0057] In addition, the control unit (400) of the charging control device (1000) can calculate the amount of additional charge to be charged to the battery and display it on a user terminal linked to the electric vehicle when it is determined that the electric vehicle cannot drive to the destination based on the calculated driving distance.

[0058] In one embodiment, when the control unit (400) of the charging control device (1000) determines that the electric vehicle cannot travel to the destination based on the calculated driving distance, it may display information about a charging station located between the electric vehicle and the destination on a user terminal linked to the electric vehicle. A detailed explanation thereof will be provided later with reference to FIG. 9.

[0059] Up to now, with reference to FIG. 2, the configuration of an electric vehicle charging control device according to another embodiment of the present disclosure has been described. Below, with reference to FIG. 3, driving information received from an electric vehicle in some embodiments of the present disclosure will be described.

[0060] FIG. 3 is a drawing for illustrating driving information of an electric vehicle received according to some embodiments of the present disclosure.

[0061] Referring to FIG. 3, the driving information obtained by the charging control system may include, for example, charging scheduling data (11), driving pattern data (12), final destination data (14) of an electric vehicle.

[0062] In one embodiment, the charging control system can acquire charging scheduling data (11) of the electric vehicle to identify the charging pattern of the driver of the electric vehicle. As a result, the charging control system can identify the capacity of the battery charged in the past and the charging interval, etc., and predict the amount of charge of the battery to be charged at present. As a result, the charging control system can recommend a differential recommended amount of charge by reflecting not only the battery status information but also the driver's charging pattern.

[0063] In addition, in one embodiment, the charging control system may acquire driving pattern data (12) of the electric vehicle and reflect the state of the battery according to the driving behavior of the driver of the electric vehicle. For example, the charging control system may determine the degree of influence received by the battery by identifying the driving time of the electric vehicle or the driving control operation of the electric vehicle.

[0064] In addition, in one embodiment, the charging control system can obtain data (13) regarding the final destination of the electric vehicle and calculate the distance from the current location of the electric vehicle to the final destination. As a result, the charging control system can determine the SoC value of the battery that may be consumed according to the distance to the final destination of the electric vehicle.

[0065] Additionally, the driving information obtained by the charging control system may include data (14) inside and outside the battery of the electric vehicle. In one embodiment, the charging control system may determine the state of the battery by obtaining the data (14) inside and outside the battery.

[0066] For example, the charging control system can acquire data regarding external temperature or external shock from external sensors, such as motion detection sensors mounted on the electric vehicle. As a result, the charging control system can reflect the state of the battery affected by external environmental factors.

[0067] Up to now, with reference to FIG. 3, driving information of an electric vehicle used in an electric vehicle control method according to some embodiments of the present disclosure has been described. Below, with reference to FIG. 4, indicators capable of expressing the state of a battery equipped in an electric vehicle being monitored according to some embodiments of the present disclosure will be described.

[0068] FIG. 4 is a diagram illustrating state information of a battery equipped in an electric vehicle that is monitored according to some embodiments of the present disclosure. With reference to FIG. 4, a charging control system can monitor the state of a battery equipped in an electric vehicle.

[0069] In this case, according to some embodiments of the present disclosure, a charging control system for monitoring the state of a battery may be implemented in conjunction with a Battery Management System (BMS). However, this may not be limited to the scope of the present disclosure.

[0070] Additionally, according to some embodiments of the present disclosure, the battery (20) monitored by the charging control system may consist of a single battery cell or may be composed of a plurality of battery cells. Although this may not be limited to the scope of the present disclosure, for convenience of explanation, the present disclosure will describe it as being set to a single battery cell.

[0071] Referring again to FIG. 4, according to some embodiments of the present disclosure, a battery (20) monitored by a charging control system may be composed of an area (21) where aging has progressed and charging is no longer possible, a currently charged area (23), and a currently chargeable area (22).

[0072] At this time, the charging control system can measure the SoH value (degree of aging) of the battery (20) as 100% because aging has not progressed with respect to the total capacity that the battery initially has.

[0073] Subsequently, as aging progresses through the charging or discharging cycle of the battery (20), the usable capacity of the battery may decrease. For example, referring to FIG. 4, the charging control system can measure the SoH value (degree of aging) of a battery that has a reduced capacity by the region (21) where charging is no longer possible from the total capacity of the existing battery as 66%. That is, the charging control system can confirm the degree of reduction in the usable capacity of the battery.

[0074] At this time, the charging control system can measure the SoC value as 100% for the reduced usable capacity of the battery (20). Additionally, with reference to FIG. 4, the charging control system can measure the SoC value as 40% for the remaining charge amount in the battery (20).

[0075] Additionally, in one embodiment, the charging control system may measure 10% as the minimum reference SoC value (24) of the battery (20). At this time, the minimum reference SoC value of the battery can be understood as the minimum amount of battery charge required to maintain the function of the electric vehicle.

[0076] In addition, in one embodiment, the charging control system can calculate the SoH value (expected lifespan) of the battery (20) using the reduction in the available capacity of the battery (20) and the minimum reference SoC value (24) of the battery (20).

[0077] Specifically, the charging control system can calculate the cycle in which the chargeable area (22) of the battery (20) decreases below the minimum reference SOC value of the battery (20) by utilizing the reduction in the available capacity of the battery (20) as the SoH value (expected lifespan) of the battery (20). Additionally, in one embodiment, the charging control system may analyze the charging pattern of the battery (20) to determine the SoH value (expected lifespan) of the battery (20) that varies according to the charging frequency of the battery (20).

[0078] In addition, in one embodiment, when the battery is a battery pack composed of multiple cells, the charging control system can calculate the SoB (Internal Variation) value of the battery by comparing state indicators such as the SOC value, temperature, and voltage discussed earlier for individual cells within the battery pack. The larger the SoB (Internal Variation) value of the battery, the lower the performance of the battery and the lower the charging efficiency may be. Therefore, the charging control system can check whether the aging of the battery is accelerated by checking the SoB (Internal Variation) value of the battery. A detailed explanation of this will be provided later with reference to FIG. 6.

[0079] In addition, in one embodiment, the charging control system can measure the SoS value (safety) of the battery. For example, the charging control system can measure the SoS value (safety) based on the battery status indicators measured earlier.

[0080] At this time, the charging control system can classify the SoS value (safety level) of the battery by grade. For example, the charging control system can classify the safety status of the battery to be monitored according to the SoS value (safety level) into a good grade, a caution grade, and a dangerous grade. In addition, the charging control system may vary the control method according to some embodiments of the present disclosure depending on the SoS value (safety level) of the monitored battery. A detailed explanation thereof will be provided later with reference to FIG. 12.

[0081] As a result, the charging control system can monitor the battery and reflect the state and performance of the battery in recommending the recommended charge amount of the battery according to the present disclosure.

[0082] Up to now, with reference to FIG. 4, various state information of a battery in an electric vehicle monitored according to some embodiments of the present disclosure has been described. Below, an electric vehicle charging control method as an embodiment of the present disclosure will be described with reference to FIG. 5 to 9.

[0083] First, FIG. 5 is an overall flowchart of an electric vehicle charging control method according to one embodiment of the present disclosure.

[0084] Referring to FIG. 5, according to one embodiment of the present disclosure, a charging control system can obtain driving information of an electric vehicle (S100). At this time, the charging control system can obtain at least one of the following data, as described in FIG. 3 above: charging scheduling data of the electric vehicle, driving pattern data of the electric vehicle, data regarding the final destination of the electric vehicle, and data detected by an external sensor of the electric vehicle.

[0085] For example, data regarding the final destination within the charging information acquired by the charging control system may include data regarding the distance and time required to reach the destination or the location of a charging station that can be passed through.

[0086] In addition, for example, data detected by external sensors of an electric vehicle within charging information received by a charging control system may include data regarding external temperature and data regarding the degree of damage to the electric vehicle caused by external impact.

[0087] Subsequently, the charging control system can monitor the state of the battery equipped in the electric vehicle (S200). At this time, the charging control system can simply obtain data regarding the remaining charge amount (SoC value) in the battery, and can determine the specific state and performance of the battery using multiple data included in the driving information obtained in the preceding step S100.

[0088] At this time, the battery status that the charging control system can determine may include, for example, the degree of battery aging (SoH), expected lifespan (SoL), internal deviation (SoB), safety (SoS), etc. However, this may not be limited to the scope of the present disclosure, and a detailed explanation thereof will be provided later through FIGS. 6 and 7.

[0089] Afterward, the charging control system can determine whether the electric vehicle can drive to its final destination (S300). At this time, the charging control system can first determine the current location of the electric vehicle and the distance to the final destination.

[0090] Subsequently, the charging control system can calculate the estimated amount of battery consumption based on the monitoring results of the current state of the battery and the distance to the final destination. As a result, the charging control system can determine whether the electric vehicle can drive to the final destination based on the amount of charge remaining in the battery. A detailed explanation of this will be provided later through Fig. 8.

[0091] At this time, if the charging control system determines that driving to the final destination is possible based on the status information of the monitored battery, it can drive to the final destination using the remaining charge in the battery.

[0092] Conversely, if the charging control system determines that driving to the final destination of the electric vehicle is impossible, it may recommend a recommended charge amount for the battery equipped in the electric vehicle (S400).

[0093] At this time, the charging control system may recommend a passing charging station capable of charging the recommended amount of charge using the driving information of the electric vehicle obtained above and the monitored battery status information. A detailed explanation of this will be provided later through Fig. 9.

[0094] Up to now, with reference to FIG. 5, the overall sequence of an electric vehicle charging control method according to one embodiment of the present disclosure has been described. Below, some operations of the electric vehicle charging control method according to one embodiment of the present disclosure will be described in detail with reference to FIGs. 6 to 9.

[0095] First, FIG. 6 is a detailed flowchart for specifically explaining the step of monitoring the state of the battery among the electric vehicle charging control methods described with reference to FIG. 4.

[0096] Referring to FIG. 6, first, the charging control system can receive the total capacity information and current SoC value of the battery in the electric vehicle (S210). Subsequently, the charging control system can determine and monitor the status and performance information of the battery using the driving information of the electric vehicle obtained in the preceding step S100.

[0097] First, the charging control system can determine the degree of aging (SoH) of the battery in the electric vehicle using the charging scheduling data of the electric vehicle (S220). For example, the charging control system can obtain the charging history of the electric vehicle from the past to the present and, as explained in FIG. 4 above, determine the extent to which the chargeable capacity of the battery has decreased due to aging, degradation, or an increase in charge / discharge cycles of the battery. A detailed explanation of this will be provided later through the example of FIG. 11a.

[0098] In addition, the charging control system can determine the extent to which the rechargeable capacity of the battery has decreased by using data regarding external temperature and external shock detected from external sensors of the electric vehicle.

[0099] For example, if the charging control system detects the external temperature as low through an external sensor of the electric vehicle, it can be seen that the internal resistance of the battery increases due to the low temperature, thereby reducing the chargeable capacity of the battery. Conversely, if the charging control system detects that the battery of the electric vehicle is continuously exposed to high temperatures, it can be seen that the chargeable capacity of the battery is reduced. A detailed explanation of this will be provided later through the example of FIG. 11b.

[0100] In addition, in one embodiment, the charging control system can identify the driver's charging habits and preferences by analyzing the amount of charge most frequently charged to the electric vehicle from the charging history. As a result, the charging control system may not only use monitoring results regarding the battery's status and performance, but may also provide a recommended charge amount for the battery according to the present disclosure based on the driver's charging patterns and preferences.

[0101] That is, the charging control system can determine the degree of aging (SoH) of a battery within an electric vehicle by observing the extent to which the chargeable capacity of the battery gradually decreases relative to the total capacity of the battery. In this case, the charging control system may measure the degree of aging (SoH) of the battery as the ratio of the decrease in the chargeable capacity of the battery relative to the factors affecting it. However, this may not be limited to the scope of the present disclosure.

[0102] In addition, the charging control system can determine the expected lifespan (SoL) of the battery using the reduction in the chargeable capacity of the battery in the electric vehicle confirmed earlier (S230).

[0103] Specifically, as described in the preceding Fig. 5, the charging control system can additionally receive the minimum reference SoC value of the battery in the electric vehicle while acquiring driving information of the electric vehicle in step S100.

[0104] As a result, in the step of determining the expected lifespan (SoL) of the battery, the charging control system can identify the point where the chargeable capacity of the battery is measured to be less than the minimum reference SOC value of the battery by utilizing the rate of decrease in the chargeable capacity of the battery. At this time, the charging control system may express the point where the chargeable capacity of the battery is measured to be less than the minimum reference SOC value of the battery as the number of charge-discharge cycles of the battery and as a period. However, this may not be limited to the scope of the present disclosure.

[0105] As a result, the charging control system monitors the SoL of the battery to determine the replacement time of the battery in advance and can reduce the risk of accidents accordingly.

[0106] In addition, in one embodiment, when the battery equipped in the electric vehicle is composed of a plurality of cells, the plurality of battery packs may be overcharged or overdischarged due to the driver's charging pattern, and a voltage imbalance may occur between the plurality of battery cells. Accordingly, the charging control system determines the internal deviation (SoB) value for the plurality of battery packs (S240) and can confirm that the performance of the plurality of battery packs that have been overcharged or overdischarged has deteriorated, thereby reducing the chargeable capacity of the plurality of battery packs.

[0107] In addition, the charging control system can determine the safety level (SoS) of the battery by comprehensively considering the battery's condition and performance indicators, such as the degree of aging (SoH), expected lifespan (SoL), and internal deviation (SoB) determined earlier (S250).

[0108] In this case, the charging control system may classify and express the SoS of the battery by grade, and in this disclosure, the SoS of the battery is described by classifying it into Good, Caution, and Danger grades. However, this may not be limited to the scope of this disclosure.

[0109] Accordingly, the charging control system of the present disclosure can determine the safety level (SoS) of the battery as one of the grades of good, caution, and danger based on the driving information of the electric vehicle obtained above and the status and performance indicators of the monitored battery. A detailed explanation thereof will be provided later through FIG. 7.

[0110] Next, FIG. 7 is a detailed flowchart for specifically explaining the step of determining the safety level (SoS) of a battery using the driving information of the electric vehicle obtained and the status and performance indicators of the monitored battery among the electric vehicle charging control method described with reference to FIG. 6.

[0111] First, the charging control system can select at least one of a plurality of battery status information, including the current SoC value of the battery in the electric vehicle, and use it as a criterion for classifying the safety level (SoS) of the battery.

[0112] Subsequently, the charging control system can classify the grade of the battery's SoS based on at least one of the multiple battery status information. For example, as an embodiment, the charging control system may set the grade based on multiple battery status information, such as the battery's SoC, SoH (Social Overhead), and SoB (Social Overhead). In this case, the charging control system can classify the grade of the battery's SoS by assigning different weights to each of the multiple status information.

[0113] According to some embodiments of the present disclosure, a charging control system can determine the safety level (SoS) of a battery based on at least one of a plurality of state information of a battery in an electric vehicle (S251, S252, S254).

[0114] At this time, if the charging control system determines the safety rating (SoS) of the battery to be good based on specific criteria (S251), it can determine whether to drive to the final destination based on the remaining charge (SoC) of the battery and the monitored battery status information (S300). A detailed explanation of this will be provided later through FIG. 8.

[0115] In addition, if the charging control system determines the safety level (SoS) of the battery to be a caution level based on the specific criteria above (S252), it may output a warning message or a caution message regarding the status of the battery to the user terminal of the electric vehicle (S253).

[0116] In addition, if the safety level (SoS) of the battery determined by the charging control system is severe (S254), the recommended charging amount and charging station recommendation functions provided to the electric vehicle can be disabled so that the recommended charging amount is not displayed on the user terminal of the electric vehicle (S255).

[0117] Additionally, in one embodiment, the charging control system may output a signal that completely controls the driving of the electric vehicle. In this case, the driving control signal of the electric vehicle transmitted by the charging control system may include, for example, a signal that prevents the recommendation of the recommended charge amount of the battery according to the present disclosure, and may include a signal that blocks the operation of a control device, such as a brake or accelerator, to completely restrict the driving of the electric vehicle. However, this may not be limited to the scope of the present disclosure.

[0118] At this time, if the charging control system does not determine the safety level (SoS) of the battery to be one of the multiple grades classified according to the present disclosure, it may again select at least one of the multiple battery status information and set it as a criterion for classifying the safety level (SoS) of the battery to determine the safety level (SoS) of the battery.

[0119] Next, FIG. 8 is a detailed flowchart for specifically explaining the step of determining whether the electric vehicle can drive to its final destination among the electric vehicle charging control methods obtained by referring to FIG. 5.

[0120] Referring to FIG. 8, according to one embodiment, the charging control system can update the monitored battery status information by reflecting the driving pattern of the driver of the electric vehicle obtained earlier (S310). Subsequently, the charging control system can calculate the driving range of the electric vehicle using the updated battery status information (S320).

[0121] As a result, the charging control system can calculate the driving range of the battery by reflecting both the SoC consumption amount according to the state of the battery and the SoC consumption amount according to the driver's driving pattern from the SoC value remaining in the battery in the electric vehicle.

[0122] Subsequently, the charging control system can determine whether the battery can drive to the final destination based on the calculated driving range (S330). At this time, the charging control system may determine that the electric vehicle cannot drive to the final destination based on the battery's current SoC value and the battery's status information according to the monitoring results.

[0123] In this case, the charging control system may display a recommended charging amount on the user terminal of the electric vehicle that enables driving to the final destination among the chargeable capacities of the battery (S400). A detailed explanation of this will be provided later through FIG. 9.

[0124] FIG. 9 is a diagram illustrating how, in an electric vehicle charging control method according to an embodiment of the present disclosure described with reference to FIG. 5, when it is determined that driving to a final destination is impossible based on the state of the battery equipped in the electric vehicle, the charging control system displays a recommended charging amount required for the battery on a user terminal.

[0125] That is, if the charging control system determines that driving to the final destination is impossible due to the current status and performance of the battery in the monitored electric vehicle, it can display data regarding the location of a charging station located between the electric vehicle's current location and the final destination, and the capacity of the battery charged at the charging station, on the user terminal of the electric vehicle.

[0126] The charging control system may recommend a differential recommended charging amount to the user terminal of the electric vehicle by referring to Fig. 9, only when serious disqualifying factors for charging the battery have been excluded by first considering the safety rating (SoS) of the battery determined in Fig. 7 above.

[0127] First, the charging control system can check whether the degree of aging (SoH) of the battery exceeds a predetermined specific value (S410). As a result, the charging control system may not recommend a high charge amount (SOC) for a battery that has already undergone significant aging.

[0128] In addition, in this case, as an embodiment, since the degree of aging (SoH) of the battery may be affected by external temperature, the charging control system may assign a higher weight to indoor charging stations than to outdoor charging stations for the recommended charging stations, thereby arranging the display of charging station candidates differently.

[0129] At this time, if the charging control system determines that the aging of the battery has progressed to a certain extent by exceeding a preset specific value (S410), the charging control system can lower the recommended charging amount according to the state of the battery, and at the same time calculate whether to increase or decrease the number of stops at the charging station for driving to the final destination (S450).

[0130] At this time, if the charging control system determines that the number of times the charging station is passed does not increase, it may not recommend a charging amount with a high SOC value (S470). For example, the charging control system may set the recommended charging amount, which is lowered according to the state of the battery, so that it does not exceed 70%.

[0131] As a result, the charging control system can maintain battery performance or improve charging efficiency by recommending an appropriate recommended charge amount sufficient to reach the final destination. Furthermore, the charging control system can prevent unnecessary charging time consumption and accelerated battery aging that can occur when simply recommending a high charge amount.

[0132] Conversely, if the charging control system determines that the number of times the charging station is passed increases with the recommended charging amount that is lowered according to the state of the battery, it can check whether a charging station equipped with a charger capable of high-speed charging is included in the recommended group of charging stations (S460).

[0133] At this time, the candidate group of recommended charging stations may also change depending on the recommended charging amount recommended by the charging control system, and for example, if it is determined that there are two or more charging stations to pass through, the candidate group of charging stations to pass through next may change depending on the recommended charging amount for each charging station.

[0134] Accordingly, if the above-mentioned group of charging stations includes a charging station capable of high-speed charging, the charging control system may not recommend an unnecessarily high SOC value for the amount of charge to be charged at the charging station to be passed through. On the other hand, if the above-mentioned group of charging stations does not include a charging station capable of high-speed charging, the charging control system may display a charging amount with a high SOC value exceeding a preset specific value for driving to the final destination on the user terminal of the electric vehicle (S440).

[0135] Returning to step S410, if the charging control system determines that the battery is in good condition because the degree of aging (SoH) of the battery does not exceed a specific value, it can analyze the charging behavior of the battery using the charging history data received in the preceding step S100. For example, if the battery is frequently overcharged within a specific period, the aging of the battery may be accelerated; therefore, the charging control system can analyze the maximum charge amount (Max SoC) or the number of charges of the battery per specific cycle to prevent in advance from providing a recommended charge amount with a high SOC value.

[0136] As a result, if the number of times the charging control system has overcharged the battery exceeds a specific number (S420), the recommended charging amount can be lowered.

[0137] Conversely, if the charging control system determines that the degree of aging (SoH) and charging behavior of the battery are good, it can also check whether the internal deviation (SoB) exceeds a specific value (S430).

[0138] As a result, if the charging control system determines that all performance indicators of the battery are good, it can display a recommended charging amount with a high SOC value on the user terminal of the electric vehicle (S440). For example, the charging control system can display a recommended charging amount of about 80%, which is typically determined to be the optimal SOC value of the battery, along with a group of recommended charging stations between the final destination and the user terminal of the electric vehicle.

[0139] In this case, as in one embodiment, the charging control system can reflect status information of the battery equipped in the electric vehicle in motion in real time. Accordingly, data regarding the charging station and charging amount displayed on the user terminal by the charging control system may be changed according to the monitoring result value regarding the location where the electric vehicle has driven or the changed state of the battery.

[0140] Up to now, an electric vehicle charging control method according to one embodiment of the present disclosure has been described with reference to FIGS. 5 to 9. Below, with reference to the example of FIG. 10, we intend to explain how a method for recommending a recommended charge amount of a battery in an electric vehicle according to some embodiments of the present disclosure is implemented as a machine knurling model.

[0141] FIG. 10 is a diagram illustrating a machine learning model that outputs a recommended charge amount based on battery status information input according to some embodiments of the present disclosure.

[0142] In one embodiment, the charging control system may replace the step of monitoring the state of the battery of FIG. 6 and the step of recommending a recommended charge amount based on the monitoring result of the battery with a machine learning model (32).

[0143] Referring to FIG. 10, the charging control system can train a machine learning model with data regarding the state of the monitored battery. At this time, the training data input to the machine learning model may include, for example, data (31) regarding the remaining charge (SoC), degree of aging (SoH), life expectancy (SoL), internal deviation (SoB), and safety (SoS) values ​​of the battery.

[0144] In addition, the charging control system may train a machine learning model (32) using charging scheduling data, driving pattern data, and battery internal and external data included in the driving information of the electric vehicle.

[0145] As a result, the charging control system can omit the step of acquiring driving information of the electric vehicle or monitoring the state of the battery every time, thereby improving the speed and accuracy of recommending the recommended charge amount of the battery according to some embodiments of the present disclosure by using only accumulated data.

[0146] In addition, as an embodiment, the step of determining whether the electric vehicle can be driven according to driving information or battery status information obtained by the charging control system may also be replaced with a machine learning model (32).

[0147] Up to now, with reference to FIG. 10, a method for applying a machine learning model to a process for recommending a recommended charge amount of a battery according to some embodiments of the present disclosure has been described. Below, battery state indicators monitored as a result of some embodiments of the present disclosure will be described with reference to the examples in FIG. 11 and FIG. 12.

[0148] First, FIGS. 11a and FIGS. 11b are drawings for illustrating the degree of aging (SoH) of a battery monitored according to some embodiments of the present disclosure.

[0149] Referring to FIG. 11a, the charging control system can confirm that the degree of aging (SoH) of the battery in the electric vehicle worsens as the charge and discharge cycles of the battery accumulate. That is, the charging control system can confirm that the chargeable capacity of the battery decreases as the charge and discharge cycles of the battery in the electric vehicle accumulate.

[0150] Additionally, referring to FIG. 11b, the charging control system can confirm that the degree of aging (SoH) of the battery varies according to the external temperature detected by the external sensor of the electric vehicle. That is, the charging control system can confirm that the degree of aging (SoH) of the battery is affected by the external temperature of the battery. At this time, the charging control system can also confirm that the degree of aging (SoH) of the battery may vary according to external shocks detected by the external sensor of the electric vehicle.

[0151] Next, FIG. 12 is a diagram illustrating the SoS rating of a battery in an electric vehicle as described in FIG. 6 and FIG. 7.

[0152] In some embodiments according to the present disclosure, the charging control system may monitor the safety status of the battery with a Safety Level (SoS) classified into three grades. For example, according to some embodiments of the present disclosure, the Safety Level (SoS) grades of the battery may be classified into a Danger level (51), a Caution level (52), and a Good level (53) in order of increasing risk. At this time, the charging control system may display a different risk level of the battery on the user terminal of the electric vehicle according to the Safety Level (SoS) grade of the battery.

[0153] In addition, the charging control system may use data within previously acquired driving information or multiple battery status and performance indicators to distinguish multiple State of Safety (SoS) grades of the battery.

[0154] Up to now, with reference to FIGS. 11 and 12, battery status indicators monitored according to some embodiments of the present disclosure have been described. Below, with reference to the example of FIG. 13, we will describe how recommended battery charge amounts and charging stations are displayed on a user terminal screen related to an electric vehicle as a result of some embodiments of the present disclosure.

[0155] FIG. 13 is a drawing for illustrating a screen in which a recommended charging amount and a charging station are displayed according to some embodiments of the present disclosure.

[0156] Referring to FIG. 13, the charging control system may display data regarding the recommended charging amount (63) of a battery and a recommended charging station (61) according to some embodiments of the present disclosure on a user terminal (60) of an electric vehicle.

[0157] In addition, the charging control system may also display status information (62) of the battery monitored according to some embodiments of the present disclosure on the user terminal (60) of the electric vehicle.

[0158] As a result, the charging control system, using the charging control method according to the present disclosure, enables the driver of an electric vehicle to consider the state of the battery more specifically, rather than just the amount of charge currently remaining in the battery (SoC), thereby reducing the risk of accidents that may occur in the charged battery.

[0159] Up to now, with reference to FIG. 13, the results of an electric vehicle charging control method according to some embodiments of the present disclosure have been described. Below, with reference to FIG. 14, a charging control system (1000) capable of implementing the electric vehicle charging control method will be described in detail as being able to be combined with a computing device.

[0160] FIG. 14 is an exemplary hardware configuration diagram showing a charging control system (1000) implemented as a computing device.

[0161] As illustrated in FIG. 14, the charging control system (1000) may include one or more processors (1100), a bus (1300), a vehicle communication interface (1400), a memory (1200) that loads a charging amount recommendation program executed by the processor (1100), and an EEPROM (1500) that stores the charging amount recommendation program (1600). However, FIG. 14 only illustrates components related to the embodiments of the present disclosure. Therefore, a person skilled in the art to which the present disclosure belongs will understand that other general-purpose components may be included in addition to the components illustrated in FIG. 14.

[0162] Additionally, depending on the case, the charging control system (1000) may be configured with some of the components shown in FIG. 14 omitted. Hereinafter, each component of the charging control system (1000) will be described.

[0163] The processor (1100) can control the overall operation of each component of the charging control system (1000). The processor (1100) may be configured to include at least one of an EVCC (Electric Vehicle Communication Controller), an ECU (Electronic Control Unit), a CPU (Central Processing Unit), an MPU (Micro Processor Unit), an MCU (Micro Controller Unit), or any other type of processor well known in the art of the present disclosure.

[0164] Additionally, the processor (1100) may perform control over at least one controller or vehicle communication network for executing an operation / method according to embodiments of the present disclosure. The charging control system (1000) may have one or more processors.

[0165] Next, the memory (1200) can store various data, commands and / or information. The memory (1200) can load a charge amount recommendation program (1600) from the EEPROM (1500) to execute an operation / method according to embodiments of the present disclosure.

[0166] Next, the bus (1300) can provide communication functions between components of the charging control system (1000). The bus (1300) can be implemented as various types of buses, such as an address bus, a data bus, and a control bus.

[0167] Next, the vehicle communication interface (1400) can support signal exchange between in-vehicle control devices and sensors. Additionally, the vehicle communication interface (1400) can support signal exchange between in-vehicle controllers. The vehicle communication interface (1400) can be configured to include vehicle communication network technologies such as CAN (Controller Area Network), LIN (Local Interconnect Network), FlexRay, and automotive Ethernet.

[0168] Next, the EEPROM (1500) may non-temporarily store a charge amount recommendation program (1600). The EEPROM (1500) may be replaced with non-volatile memory such as ROM (Read Only Memory), EPROM (Erasable Programmable ROM), flash memory, a hard disk, a removable disk, or any form of computer-readable recording medium well known in the art to which this disclosure belongs.

[0169] Next, the charge amount recommendation program (1600) may include one or more instructions that cause the processor (1100) to perform an operation / method according to various embodiments of the present disclosure when loaded into memory (1200). That is, the processor (1100) can perform an operation / method according to various embodiments of the present disclosure by executing the loaded instructions.

[0170] Various embodiments of the present disclosure and effects according to those embodiments have been described with reference to FIGS. 1 to 14. The effects according to the technical concept of the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by a person skilled in the art from the description below.

[0171] The technical concept of the present disclosure described above may be implemented as computer-readable code on a computer-readable medium. The computer program recorded on the computer-readable recording medium may be transmitted to another computing device via a network such as the Internet and installed on the other computing device, thereby being used on the other computing device.

[0172] Although operations are depicted in a specific order in the drawings, it should not be understood that the operations must necessarily be executed in the specific order depicted or in a sequential order, or that all depicted operations must be executed to obtain the desired result. Although embodiments of the present disclosure have been described above with reference to the attached drawings, those skilled in the art will understand that the present invention may be practiced in other specific forms without altering the technical concept or essential features thereof. Therefore, the embodiments described above should be understood as illustrative in all respects and not restrictive. The scope of protection of the present invention shall be interpreted by the claims below, and all technical concepts within the equivalent scope shall be interpreted as being included within the scope of rights of the technical concept defined by the present disclosure.

Claims

Claim 1 A motor control method comprising: a step of sampling a motor output signal, wherein the motor output signal includes a pattern section; a step of calculating a first current consumption of a first section included in the pattern section and a second current consumption of a second section included in the pattern section using the sampled motor output signal; and a step of variablely controlling the phase of a micro angle tick for controlling a motor based on a result of comparing the first current consumption and the second consumption, wherein the first section is a section prior to the pattern change angle of the motor output signal and the second section is a section after the pattern change angle. Claim 2 A motor control method according to claim 1, wherein the pattern section is a section of the motor output signal corresponding to a section of the composite signal generated using a Hall sensor output signal, and the Hall sensor output signal is a signal for detecting rotation of the rotor of the motor. Claim 3 A motor control method according to claim 1, wherein the sampling step includes the step of sampling the motor output signal of the pattern interval for each reference angle, and the reference angle is determined based on the period of the micro-angle tick. Claim 4 In paragraph 3, the step of calculating the first current consumption and the second current consumption includes the step of integrating the sampled motor output signal for each angle interval to calculate the current consumption for each angle interval, wherein the angle interval is a part of the pattern interval divided for each reference angle, a motor control method. Claim 5 A motor control method according to claim 1, wherein the variable control step includes the step of controlling the phase of the micro-angle tick so as to reduce the difference between the first current consumption and the second current consumption. Claim 6 A motor control method according to claim 5, wherein the variable control step comprises the step of retarding the phase of the micro-angle tick when the first current consumption is greater than the second current consumption, and advancing the phase of the micro-angle tick when the second current consumption is greater than the first current consumption. Claim 7 A motor control method according to claim 1, wherein the micro-angle tick is a pulse generated in equal numbers whenever the pattern of a composite signal generated using a Hall sensor output signal is changed. Claim 8 A motor control device comprising: a current consumption calculation unit that samples a motor output signal including a pattern section and calculates a first current consumption of a first section included in the pattern section and a second current consumption of a second section included in the pattern section using the sampled motor output signal; and a phase control unit that variably controls the phase of a micro angle tick for controlling a motor based on a result of comparing the first current consumption and the second consumption, wherein the first section is a section prior to the pattern change angle of the motor output signal and the second section is a section after the pattern change angle.

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