System and method for determining and managing battery degradation

Abstract

In accordance with some embodiments set forth in the present disclosure, a computing system may include an interface circuit; and at least one processor operably connected to the interface circuit, where the at least one processor is configured to: obtain battery data relating to a battery of the vehicle; determining a regenerative braking level of the vehicle based on the battery data; adjusting a driving strategy of the vehicle based on the regenerative braking level; and controlling driving of the vehicle based on the regenerative braking level and the driving strategy.

Description

TECHNICAL FIELD

[0001] Cross Reference to Related Applications

[0002] This application claims priority to Korean Patent Application No. 10-2023-0155379, filed on November 10, 2023, and Korean Patent Application No. 10-2023-0114042, filed on August 29, 2023, the entire contents of which are incorporated herein by reference for all purposes. TECHNICAL FIELD

[0003] The present disclosure relates to a system and method for determining battery degradation caused by regenerative braking. BACKGROUND

[0004] As the demand for environmentally friendly vehicles increases, electric vehicles (EVs) using a battery such as a lithium-ion secondary battery as an energy source are rapidly replacing existing internal combustion engine vehicles. In addition, as artificial intelligence technology and various sensor technologies advance, research and development to improve the performance of hardware and software related to autonomous driving systems are also actively being conducted.

[0005] An autonomous driving system that supports autonomous driving of a vehicle has been developed or provided in the form of an autonomous driving platform including various sensors and control units. Some electric vehicle manufacturers are mass-producing or developing autonomous driving electric vehicles based on autonomous driving platforms.

[0006] Regenerative braking can refer to a braking method in which a motor is used to charge a battery when a vehicle having a battery as an energy source and a motor as a driving device is braked. Regenerative braking can be performed at different levels, and the braking force of the vehicle and the charging amount of the battery can vary depending on the level of regenerative braking. A driving control device of an electric vehicle can determine an appropriate regenerative braking level, and can control driving of the electric vehicle accordingly. However, regenerative braking can inevitably cause degradation of the battery because the battery is repeatedly charged and discharged. Therefore, the battery degrades faster compared to when regenerative braking is not used. This rapid degradation of the battery results in the need to replace the battery more frequently, resulting in more emissions and / or greenhouse gases being generated during battery production. Such emissions and / or greenhouse gases can adversely affect the environment, such as by causing climate change. SUMMARY

[0007] TECHNICAL PROBLEM

[0008] One object of the embodiments disclosed herein is to provide a battery management system, a vehicle, a battery management method, and a computer program that can take into account regenerative braking of a vehicle when predicting a degree of battery degradation, and in some instances, adjust charging and / or discharging of a battery to reduce battery degradation. By predicting a degree of battery degradation based on a regenerative braking level and adjusting charging and / or discharging of a battery to reduce battery degradation, an overall life of a battery can be increased, resulting in a reduction in a level of emissions and / or greenhouse gases produced during production of the battery. Furthermore, the technology described herein can be implemented in automated vehicle platforms of many types of vehicles, resulting in widespread improvements in energy efficiency.

[0009] One object of the embodiments disclosed herein is to provide a computing system, a vehicle, a method for operating a computing system, and a computer program that can determine a regenerative braking and / or driving strategy of a vehicle taking into account degradation of a battery.

[0010] The technical problems to be solved by the present disclosure are not limited to the above-mentioned technical problems, and any other technical problems not mentioned will be clearly understood by those skilled in the art from the following description.

[0011] Technical solutions

[0012] Aspects of the present disclosure can include a computing system. The computing system can include at least one processor configured to: receive battery data related to a battery of a vehicle; determine a regenerative braking level of the vehicle based on the battery data; adjust a driving strategy of the vehicle based on the regenerative braking level; and control driving of the vehicle based on the driving strategy.

[0013] In some examples, the battery data includes a state of charge (SOC) level of the battery, and the at least one processor is further configured to determine the regenerative braking level based on a relationship inversely proportional to the SOC level.

[0014] In some examples, the at least one processor is further configured to calculate a discharging amount of the SOC level based on driving of the vehicle, and calculate a charging amount of the SOC level based on regenerative braking of the vehicle, wherein the regenerative braking level is determined based on the discharging amount and the charging amount.

[0015] In some examples, the at least one processor is further configured to calculate a predicted discharging amount and a predicted charging amount of the SOC level after a predetermined time elapses, wherein calculating the predicted discharging amount and the predicted charging amount is based on the discharging amount and the charging amount; and determine a next level of the regenerative braking level based on the predicted discharging amount and the predicted charging amount.

[0016] In some cases, adjusting the driving strategy of the vehicle based on the regenerative braking level includes adjusting one or more of a driving speed, a driving route, a driving responsiveness, or an inter-vehicle distance setting of the vehicle.

[0017] In some examples, adjusting the driving strategy of the vehicle based on the regenerative braking level includes increasing the driving speed and / or decreasing the inter-vehicle distance setting of the vehicle when the regenerative braking level is increased.

[0018] In some examples, adjusting the driving strategy of the vehicle based on the regenerative braking level includes increasing the driving responsiveness and / or setting the driving route to a route requiring more braking of the vehicle when the regenerative braking level is increased.

[0019] In some examples, adjusting the driving strategy of the vehicle based on the regenerative braking level includes decreasing the driving speed and / or increasing the inter-vehicle distance setting of the vehicle when the regenerative braking level is decreased.

[0020] In some examples, adjusting the driving strategy of the vehicle based on the regenerative braking level includes decreasing the driving responsiveness to reduce acceleration events and / or braking events and / or setting the driving route to a route requiring less braking of the vehicle when the regenerative braking level is decreased.

[0021] In some examples, the at least one processor is further configured to: maintain the same regenerative braking level in response to a change in the battery data; and adjust the driving strategy based on a difference in the amount of battery charging due to maintaining the regenerative braking level.

[0022] In some examples, the at least one processor is further configured to: determine whether an increase in the regenerative braking level is needed in a next time period based on a change in the battery data in a current time period; determine the regenerative braking level in the next time period in the same manner as in the current time period in a case where it is determined that the increase is needed; and adjust the driving strategy in the next time period by reflecting an amount of reduction in the amount of battery charging due to maintaining the regenerative braking level.

[0023] Some aspects of the disclosure relate to a vehicle, comprising: a battery and a computing system.

[0024] Some aspects of the disclosure relate to a method of controlling a vehicle, the method comprising: receiving, by one or more processors, battery data related to a battery of the vehicle; determining, by the one or more processors, a regenerative braking level of the vehicle based on the battery data; adjusting, by the one or more processors, a driving strategy of the vehicle based on the regenerative braking level; and controlling, by the one or more processors, driving of the vehicle based on the driving strategy.

[0025] In some examples, the battery data includes a state of charge (SOC) level of the battery, and wherein determining the regenerative braking level includes determining the regenerative braking level based on a relationship inversely proportional to the SOC level.

[0026] In some examples, determining the regenerative braking level includes calculating a discharge amount of the SOC level based on driving of the vehicle, and calculating a charge amount of the SOC level based on regenerative braking of the vehicle, wherein the regenerative braking level is determined based on the discharge amount and the charge amount.

[0027] In some examples, determining the regenerative braking level includes maintaining a same regenerative braking level in response to a change in the battery data, and adjusting the driving strategy includes adjusting the driving strategy taking into account a difference in battery charge amount due to maintaining the regenerative braking level.

[0028] In some examples, adjusting the driving strategy of the vehicle based on the regenerative braking level includes adjusting one or more of a driving speed, a driving route, a driving responsiveness, or an inter-vehicle distance setting of the vehicle.

[0029] In some examples, adjusting the driving strategy of the vehicle based on the regenerative braking level includes increasing the driving speed of the vehicle, decreasing the inter-vehicle distance setting, increasing the driving responsiveness, and / or setting the driving route to a route requiring more braking of the vehicle when the regenerative braking level is increased.

[0030] In some examples, adjusting the driving strategy of the vehicle based on the regenerative braking level includes decreasing the driving speed of the vehicle, increasing the inter-vehicle distance setting, decreasing the driving responsiveness to reduce acceleration events and / or braking events, and / or setting the driving route to a route requiring less braking of the vehicle when the regenerative braking level is decreased.

[0031] Some aspects of the disclosure relate to a non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to: obtain battery data related to a battery of a vehicle; determine a regenerative braking level of the vehicle based on the battery data; adjust a driving strategy of the vehicle based on the regenerative braking level; and control driving of the vehicle based on the driving strategy.

[0032] According to some embodiments, a computing system can include interface circuitry; and at least one processor operably coupled to the interface circuitry, wherein the at least one processor is configured to obtain battery data related to a battery of a vehicle, determine a regenerative braking level of the vehicle based on the battery data, adjust a driving strategy of the vehicle based on the regenerative braking level, and control driving of the vehicle based on the regenerative braking level and the driving strategy.

[0033] According to some embodiments, the battery data can include a state of charge (SOC) level of the battery, and the at least one processor can be configured to determine the regenerative braking level based on a relationship inversely proportional to the SOC level.

[0034] According to some embodiments, the at least one processor can be configured to calculate a discharge amount of the SOC level according to travel of the vehicle, and calculate a charge amount of the SOC level according to regenerative braking of the vehicle, and determine the regenerative braking level based on the discharge amount and the charge amount.

[0035] According to some embodiments, the at least one processor can be configured to calculate a predicted discharge amount and a predicted charge amount of the SOC level after a predetermined time based on the discharge amount and the charge amount, determine a next level of the regenerative braking level based on the predicted discharge amount and the predicted charge amount, and maintain the next level until the predetermined time elapses.

[0036] According to some embodiments, the at least one processor can be configured to positively adjust the travel strategy considering an increase in braking force of the vehicle in the case where the regenerative braking level is increased, and defensively adjust the travel strategy considering a decrease in the braking force of the vehicle in the case where the regenerative braking level is decreased.

[0037] According to some embodiments, the at least one processor can be configured to adjust the travel strategy by changing at least one of a travel speed, a travel route, a travel responsiveness, or an inter-vehicle distance setting of the vehicle according to an increase or a decrease in the regenerative braking level.

[0038] According to some embodiments, the at least one processor can be configured to maintain the same regenerative braking level in response to a change in the battery data, and adjust the travel strategy considering a difference in battery charge amount due to the maintenance of the regenerative braking level.

[0039] According to some embodiments, the at least one processor can be configured to determine whether the regenerative braking level needs to be increased in a next period based on a change in the battery data in a current period, determine the regenerative braking level in the next period in the same manner as in the current period in the case where it is determined that the regenerative braking level needs to be increased, and adjust the travel strategy in the next period by reflecting an amount of reduction in the battery charge amount due to the maintenance of the regenerative braking level.

[0040] According to some embodiments, a vehicle can include a battery, and a computing system configured to acquire battery data related to the battery, determine a regenerative braking level of the vehicle based on the battery data, adjust a travel strategy of the vehicle based on the regenerative braking level, and control travel of the vehicle based on the regenerative braking level and the travel strategy.

[0041] According to some embodiments, the battery data can include a state of charge (SOC) level of the battery, and the computing system can be configured to determine the regenerative braking level based on a relationship inversely proportional to the SOC level.

[0042] According to some embodiments, the computing system can be configured to calculate a discharge amount of the SOC level from driving of the vehicle, and calculate a charge amount of the SOC level from regenerative braking of the vehicle, based on the discharge amount and the charge amount, determine a next level of the regenerative braking level, and maintain the next level until a predetermined time elapses.

[0043] According to some embodiments, the computing system can be configured to calculate a predicted discharge amount and a predicted charge amount of the SOC level after the predetermined time elapses based on the discharge amount and the charge amount, determine the next level of the regenerative braking level based on the predicted discharge amount and the predicted charge amount, and maintain the next level until the predetermined time elapses.

[0044] According to some embodiments, the computing system can be configured to positively adjust the driving strategy considering an increase in braking force of the vehicle in the case where the regenerative braking level is increased, and defensively adjust the driving strategy considering a decrease in the braking force of the vehicle in the case where the regenerative braking level is decreased.

[0045] According to some embodiments, the computing system can be configured to adjust the driving strategy by changing at least one of a driving speed, a driving route, a driving responsiveness, or an inter-vehicle distance setting of the vehicle according to an increase or a decrease in the regenerative braking level.

[0046] According to some embodiments, the computing system can be configured to maintain the same regenerative braking level in response to a change in the battery data, and adjust the driving strategy considering a difference in battery charge amount due to the maintenance of the regenerative braking level.

[0047] According to some embodiments, the computing system can be configured to determine whether an increase in the regenerative braking level is required in a next period based on a change in the battery data in a current period, determine the regenerative braking level in the next period in the same manner as in the current period in the case where it is determined that the increase is required, and adjust the driving strategy in the next period by reflecting an amount of reduction in the battery charge amount due to the maintenance of the regenerative braking level.

[0048] According to some embodiments, a method for operating a computing system can include the operations of obtaining battery data related to a battery of a vehicle, determining a regenerative braking level of the vehicle based on the battery data, adjusting a driving strategy of the vehicle based on the regenerative braking level, and controlling driving of the vehicle based on the regenerative braking level and the driving strategy.

[0049] According to some embodiments, the battery data can include a state of charge (SOC) level of the battery, and the operation of determining the regenerative braking level can include an operation of determining the regenerative braking level based on a relationship inversely proportional to the SOC level.

[0050] According to some embodiments, the operation of determining the regenerative braking level can include operations of calculating a discharge amount of the SOC level according to travel of the vehicle, and calculating a charge amount of the SOC level according to regenerative braking of the vehicle, and determining the regenerative braking level based on the discharge amount and the charge amount.

[0051] According to some embodiments, the operation of determining the regenerative braking level can include operations of calculating a predicted discharge amount and a predicted charge amount of the SOC level after a predetermined time elapses based on the discharge amount and the charge amount, determining a next level of the regenerative braking level based on the predicted discharge amount and the predicted charge amount, and maintaining the next level until the predetermined time elapses.

[0052] According to some embodiments, the operation of adjusting the travel strategy can include operations of positively adjusting the travel strategy in consideration of an increase in braking force of the vehicle in the case where the regenerative braking level is increased, and defensively adjusting the travel strategy in consideration of a decrease in braking force of the vehicle in the case where the regenerative braking level is decreased.

[0053] According to some embodiments, the operation of adjusting the travel strategy can include an operation of adjusting the travel strategy by changing at least one of a travel speed, a travel route, a travel responsiveness, or a car-to-car distance setting of the vehicle according to an increase or a decrease in the regenerative braking level.

[0054] According to some embodiments, the operation of determining the regenerative braking level can include an operation of maintaining the same regenerative braking level in response to a change in the battery data, and the operation of adjusting the travel strategy can include an operation of adjusting the travel strategy in consideration of a difference in battery charge amount due to the maintenance of the regenerative braking level.

[0055] According to some embodiments, the operation of determining the regenerative braking level can include operations of determining whether an increase in the regenerative braking level is required in a next period based on a change in the battery data in a current period, and determining the regenerative braking level in the next period in the same manner as in the current period in the case where it is determined that the increase is required, and the operation of adjusting the travel strategy can include an operation of adjusting the travel strategy in the next period by reflecting an amount of decrease in battery charge amount due to the maintenance of the regenerative braking level.

[0056] According to some embodiments, a computer program stored in a computer readable medium can include instructions which, when executed by at least one processor, cause the at least one processor to perform operations of: acquiring battery data related to a battery of a vehicle; determining a regenerative braking level of the vehicle based on the battery data; adjusting a travel strategy of the vehicle based on the regenerative braking level; and controlling travel of the vehicle based on the regenerative braking level and the travel strategy.

[0057] According to some embodiments, the battery data can include a state of charge (SOC) level of the battery, and the operation of determining the regenerative braking level can include an operation of determining the regenerative braking level based on a relationship inversely proportional to the SOC level.

[0058] According to some embodiments, the operation of determining the regenerative braking level can include operations of: calculating a discharge amount of the SOC level from travel of the vehicle, and calculating a charge amount of the SOC level from regenerative braking of the vehicle; and determining the regenerative braking level based on the discharge amount and the charge amount.

[0059] According to some embodiments, the operation of determining the regenerative braking level can include operations of: calculating a predicted discharge amount and a predicted charge amount of the SOC level after a predetermined time based on the discharge amount and the charge amount; determining a next level of the regenerative braking level based on the predicted discharge amount and the predicted charge amount; and maintaining the next level until the predetermined time elapses.

[0060] According to some embodiments, the operation of adjusting the travel strategy can include operations of: positively adjusting the travel strategy in consideration of an increase in braking force of the vehicle in case that the regenerative braking level increases; and defensively adjusting the travel strategy in consideration of a decrease in braking force of the vehicle in case that the regenerative braking level decreases.

[0061] According to some embodiments, the operation of adjusting the travel strategy can include an operation of adjusting the travel strategy by changing at least one of a travel speed, a travel route, a travel responsiveness, or an inter-vehicle distance setting of the vehicle according to an increase or a decrease in the regenerative braking level.

[0062] According to some embodiments, the operation of determining the regenerative braking level can include an operation of maintaining the same regenerative braking level in response to a change in the battery data, and the operation of adjusting the travel strategy can include an operation of adjusting the travel strategy in consideration of a difference in battery charge amount due to the maintenance of the regenerative braking level.

[0063] According to some embodiments, the operation of determining the regenerative braking level can include operations of determining whether the regenerative braking level needs to be increased in the next period based on a change in the battery data in the current period, and determining the regenerative braking level in the next period in the same manner as in the current period in the case where it is determined that the increase is needed, and the operation of adjusting the travel strategy can include an operation of adjusting the travel strategy in the next period by reflecting an amount of reduction in the battery charge due to maintaining the regenerative braking level.

[0064] Advantages

[0065] According to some embodiments, it is possible to provide a battery management system, a vehicle, a battery management method, and a computer program that can consider regenerative braking of a vehicle when predicting a degree of deterioration of a battery.

[0066] According to some embodiments, it is possible to provide a computing system, a vehicle, a method for operating a computing system, and a computer program that can determine regenerative braking and / or a travel strategy of a vehicle considering deterioration of a battery.

[0067] Effects of the present disclosure are not limited to the above-mentioned effects, and it is understood to include all possible effects deduced from the configurations of the present disclosure described in the detailed description or claims of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0068] Figure 1 FIG. 1 is a diagram illustrating a vehicle management system according to some embodiments disclosed herein.

[0069] Figure 2 FIG. 2 is a diagram illustrating a process of performing regenerative braking in a vehicle according to some embodiments disclosed herein.

[0070] Figure 3 FIG. 3 is a diagram illustrating components and functions of a battery according to some embodiments disclosed herein.

[0071] Figure 4 FIG. 4 is a diagram illustrating a process of predicting a degree of deterioration of a battery based on an estimated regenerative braking level according to some embodiments disclosed herein.

[0072] Figure 5 FIG. 5 is a diagram illustrating a deterioration prediction model according to some embodiments disclosed herein.

[0073] Figure 6 FIG. 6 is a diagram illustrating operations constituting a battery management method according to some embodiments disclosed herein.

[0074] Figure 7 FIG. 7 is a diagram illustrating components and functions of a computing system according to some embodiments disclosed herein.

[0075] Figure 8 FIG. 16 is a diagram illustrating a process of determining a regenerative braking level and adjusting a travel strategy according to some embodiments disclosed herein.

[0076] Figure 9 FIG. 17 is a diagram illustrating a process of adjusting only a travel strategy while maintaining a regenerative braking level according to some embodiments disclosed herein.

[0077] Figure 10 FIG. 18 is a diagram illustrating operations constituting a method for operating a computing system according to some embodiments disclosed herein. DETAILED DESCRIPTION

[0078] The present disclosure is described below with reference to the accompanying drawings. However, it is not intended to limit the present disclosure to specific embodiments, but it is to be understood that various modifications, equivalents, and / or alternatives to the embodiments described herein are included.

[0079] It should be understood that the embodiments of the present disclosure and the terms used therein are not intended to limit the technical features set forth herein to particular embodiments and include various changes, equivalents, or replacements of the embodiments according to the technical features set forth herein. The similar reference numerals can be used to refer to similar or related elements throughout the drawings and specification. It should be understood that the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise.

[0080] As used herein, each of such phrases as "A or B," "at least one of A and B," "at least one of A or B," "A, B, or C," "at least one of A, B, and C," and "at least one of A, B, or C," can include all possible combinations of the items enumerated in the phrase. As used herein, such terms as "first" and "second" are used to simply identify the corresponding components without imposing an ordinal restriction on the components (e.g., importance or sequence). As used herein, such terms as "A and / or B" can include at least one of A, at least one of B, or both A and B.

[0081] It should be understood that if an element (for example, a first element) is referred to as being "connected to" or "coupled to" another element (for example, a second element) without qualification, it should be understood that the element can be directly connected to the other element or connected to the other element via a third element.

[0082] The method according to various embodiments of the present disclosure can be included and provided in a computer program product. The computer program product can be traded as a product between a seller and a buyer. The computer program product can be distributed in the form of a machine-readable storage medium (e.g., compact disc read only memory (CD-ROM)), or be distributed online via an application store (e.g., Google Play Store™, Apple App Store™, or Microsoft Store). If distributed online, at least part of the computer program product can be temporarily generated or at least temporarily stored in the memory of the manufacturer's server, an application store, or a relay server.

[0083] According to various embodiments of the present disclosure, each component (e.g., a module or a program) of the above-described components can include a single entity or multiple entities, or some of the multiple entities can be omitted from the components. According to various embodiments of the present disclosure, the above-described components or operations can be added, removed, or modified, or one or more other components or operations can be added. Alternatively or additionally, a plurality of components (e.g., modules or programs) can be integrated into a single component. In this case, the integrated component can still perform one or more functions of each of the plurality of components in the same or similar manner as they are performed by a corresponding one of the plurality of components before the integration. According to various embodiments of the present disclosure, operations performed by the module, the program, or another component can be executed sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations can be executed in a different order or omitted, or one or more other operations can be added.

[0084] Figure 1 FIG. 1 is a diagram illustrating a vehicle management system according to some embodiments disclosed herein.

[0085] Referring to Figure 1 The vehicle management system 1 can include a vehicle 10, a network 20, an autonomous travel management server 30, and an energy management server 40. For example, the vehicle management system 1 can refer to a system that manages the vehicle 10 by analyzing and / or managing data related to travel and energy of the vehicle 10 collected by the autonomous travel management server 30 and the energy management server 40 through the network 20.

[0086] The vehicle 10 can include a communication module 100, a sensor module 200, a computing system 300, a battery 400, and a drive system 500. For example, the vehicle 10 can be an electric vehicle (EV) or a hybrid electric vehicle (HEV) that generates driving force using electric energy. Also, according to various embodiments, the vehicle 10 can include a vehicle equipped with an autonomous travel function, and the communication module 100, the sensor module 200, and the computing system 300 can be implemented in the form of an autonomous travel platform, but are not limited thereto.

[0087] The communication module 100 can exchange data with the outside of the vehicle 10. For example, the communication module 100 establishes a wired and / or wireless communication channel, and can exchange various data with the outside through the established communication channel. In particular, the communication module 100 can access an external device of the vehicle 10 via the network 20.

[0088] The sensor module 200 can detect objects located around the vehicle 10. For example, the sensor module 200 can include a camera sensor for detecting surrounding objects, a global navigation satellite system (GNSS) sensor for assisting mapping, perception, occupancy grid generation, and / or path planning functions, a RADAR sensor for detecting nearby vehicles, an ultrasonic sensor for parking assistance and / or occupancy grid generation, a LIDAR sensor for object and pedestrian detection, emergency braking, collision avoidance, and / or other functions, an inertial measurement unit (IMU) sensor including an accelerometer, a magnetometer, a gyroscope, and / or a magnetic compass, a vibration sensor, a temperature sensor, and / or a speed sensor.

[0089] The computing system 300 can manage the operation of the vehicle 10 and functions provided by the vehicle 10 as a whole. To this end, the computing system 300 can control and / or manage the operation of the communication module 100, the sensor module 200, the battery 400, and / or the drive system 500.

[0090] The computing system 300 can process various operations related to the vehicle 10, and can execute programs, software, or instructions. According to an embodiment, the computing system 300 can process calculations related to travel control of the vehicle 10 and / or calculations related to energy management functions. For example, calculations related to travel control of the vehicle 10 can include calculations for judging / determining a travel strategy, a travel route, movement, etc. of the vehicle 10. According to some embodiments, the computing system 300 can determine a regenerative braking level of the vehicle 10 based on battery data including a state of charge (SOC) of the battery 400, etc., and can adjust a travel strategy of the vehicle 10 based on the regenerative braking level.

[0091] The computing system 300 can include at least one processor for arithmetic processing and instruction execution, and an interface circuit for interacting with other components of the vehicle 10. According to an embodiment, the communication scheme of the interface circuit can be a device-to-device communication scheme such as a bus, a general purpose input output (GPIO), a serial peripheral interface (SPI), or a mobile industry processor interface (MIPI).

[0092] The at least one processor of the computing system 300 can have a structure for executing instructions for implementing processes processed inside the vehicle 10. The at least one processor can be implemented as a general-purpose microprocessor for processing various operations or an array of a plurality of logic gates, and can consist of a single processor or a plurality of processors. For example, the at least one processor can be implemented in the form of a microprocessor, a central processing unit (CPU), a graphic processing unit (GPU), an application processor (AP), an application specific integrated process (ASIC), or a combination thereof.

[0093] The at least one processor of the computing system 300 can be configured separately from or integrally with a memory (not shown) configured to store instructions, and can process various operations by executing the instructions stored in the memory. The memory can store various data, instructions, mobile applications, computer programs, etc. For example, the memory can be implemented as a non-volatile memory such as a ROM, a PROM, an EPROM, an EEPROM, a flash memory, a PRAM, a MRAM, a RRAM, a FRAM, etc., or a volatile memory such as a DRAM, a SRAM, a SDRAM, a PRAM, a RRAM, a FeRAM, etc., or can be implemented in the form of an HDD, an SSD, an SD, a microSD, etc., or a combination thereof. In some examples, the computing system 300 can be implemented as a system on chip (SoC).

[0094] The battery 400 can supply power and / or electric energy to the vehicle 10. For example, the battery 400 can be a rechargeable secondary battery that is discharged while supplying power to the vehicle 10 and is charged by a battery charging device, and can be, for example, a lithium ion battery, but is not limited thereto. According to some embodiments, the battery 400 can be charged by regenerative braking of the vehicle 10. According to some embodiments, the battery 400 can include a battery cell, a battery module, a battery pack, and / or a battery rack, and can include a battery management system (BMS) that manages the battery cell, the battery module, the battery pack, etc.

[0095] The battery management system (BMS) can be a battery management system that manages overall operations / functions of the battery 400. According to embodiments, the battery management system (BMS) can process operations related to an energy management function, and in some cases, the battery management system (BMS) can provide an arithmetic result to the computing system 300. According to some embodiments, the battery management system of the battery 400 can determine whether regenerative braking of the vehicle 10 occurs, and predict a degree of degradation of the battery pack based on data related to the regenerative braking.

[0096] The driving system 500 can control the travel and / or movement of the vehicle 10. For example, the driving system 500 can control the operation of actuators related to braking, travel, and posture of the vehicle 10. According to some embodiments, the driving system 500 can include a braking system that controls the operation of actuators related to braking, a posture control system that controls the operation of actuators to stably maintain the posture of the vehicle body, a steering system that controls the operation of actuators for controlling lateral movement of the vehicle, a transmission system that controls the operation of actuators for automatic shifting, and / or an engine management system that controls the operation of actuators for controlling the travel speed of the vehicle, but is not limited thereto.

[0097] According to some embodiments, the driving system 500 can control the travel and / or movement of the vehicle 10 in response to a control instruction from the computing system 300. For example, the driving system 500 can control the travel and / or movement of the vehicle 10 in response to a control instruction based on an arithmetic result (e.g., an arithmetic / execution result of autonomous travel software) of the computing system 300. According to some embodiments, the driving system 500 can travel the vehicle 10 based on a regenerative braking level and a travel strategy set by the computing system 300.

[0098] The network 20 can refer to a data communication network that supports communication between the vehicle 10, the autonomous travel management server 30, and the energy management server 40. For example, the network 20 can include a wired network, a wireless network, or a combination thereof, but is not limited thereto, and can be different types of networks to the extent that data exchange is supported. According to some embodiments, the wired network can include a local or wide area Internet that supports a TCP / IP protocol. The wireless network can include a base station-based wireless communication network, a satellite communication network, a local area wireless communication network such as Wi-Fi, or a combination thereof.

[0099] According to some embodiments, the network 20 can include a 2G to 5G network, an LTE network, a global system for mobile communications (GSM) network, a code division multiple access (CDMA) network, an evolution-data optimized (EVDO) network, a public land mobile network, and / or other networks. According to some embodiments, the network 20 can include a local area network (LAN), a wireless local area network (WLAN), a wide area network, a metropolitan area network (MAN), a public switched telephone network (PSTN), an ad hoc network, a managed IP network, a virtual private network, an intranet, the Internet, a fiber-optic based network, and / or a combination thereof, or other types of networks.

[0100] According to some embodiments, the autonomous driving management server 30 and the energy management server 40 can include a communication module, a processor, a database, etc. The autonomous driving management server 30 and the energy management server 40 can acquire vehicle-related data from the vehicle 10 through the communication module. For example, the vehicle-related data can include driving data related to the driving of the vehicle 10 and / or battery data related to the battery 400 of the vehicle 10. The autonomous driving management server 30 and the energy management server 40 can record the vehicle-related data provided from the vehicle 10 in the database. For example, the processor of the autonomous driving management server 30 or the energy management server 40 can include a central processing unit (CPU), an application processor (AP), a graphic processing unit (GPU), a neural processing unit (NPU), and an image signal processor, etc., and can perform various data processing or arithmetic operations.

[0101] According to some embodiments, the autonomous driving management server 30 can support the update of autonomous driving software installed in the vehicle 10, the update of a navigation map, the driving control of the vehicle 10, etc., and can store driving data, black box video data, etc. provided from the vehicle 10 for a certain period of time. In addition, the autonomous driving management server 30 can be configured to perform various functions related to the processing, management, and storage of information or data related to the driving of the vehicle 10.

[0102] According to some embodiments, the driving control for the vehicle 10 can mean to control driving-related variables of the vehicle 10, such as a position, a speed, an acceleration, a driving direction, an RPM of an engine / motor, a gear ratio, a suspension damping, and a regenerative braking level, based on driving data of the vehicle 10. For example, the driving data can include object data about objects around the vehicle 10 and movement data about the movement of the vehicle 10. According to some embodiments, the object data can include a type and a number of surrounding objects, a distance to the vehicle 10, a position relative to the vehicle 10, a ground position, a relative speed, a ground speed, a relative acceleration, a ground acceleration, etc. The movement data can include a position, a movement path, a distance traveled, a speed, an acceleration, a steering angle, a yaw, a pitch, a roll, etc. of the vehicle 10.

[0103] According to some embodiments, the autonomous driving management server 30 can perform the driving control of the vehicle 10 by remotely controlling the acceleration, the deceleration, the steering, and combinations thereof of the vehicle 10. According to some embodiments, the autonomous driving management server 30 can execute driving control software that remotely controls the driving of the vehicle 10. For example, the driving control software can provide an instruction for controlling the driving system 500 to the computing system 300 of the vehicle 10 based on the driving data provided from the communication module 100 and / or the sensor module 200 of the vehicle 10. In addition, the driving control software can additionally consider the battery data provided from the battery 400 when performing the driving control of the vehicle 10.

[0104] According to some embodiments, the energy management server 40 can support an update of energy management software installed in the vehicle 10, machine learning for an energy-related artificial intelligence model, etc., and can store battery data provided from the vehicle 10, artificial intelligence model parameters, etc., for a certain period of time. In addition, the energy management server 40 can be configured to perform various functions related to processing, management, and storage of information or data related to the battery 400 of the vehicle 10.

[0105] According to some embodiments, the energy management function performed for the vehicle 10 can mean an operation of generating and / or providing a state diagnosis, a life prediction, an operation control (e.g., cell balancing), a charging guideline, etc., of the battery 400 based on battery data provided from the battery 400 of the vehicle 10. For example, the battery data can include voltage data, current data, temperature data, state of charge (SOC) data, state of health (SOH) data, and combinations thereof, and can further include cumulative charge current amount, cumulative discharge current amount, cumulative charge power, cumulative discharge power, insulation resistance, relay state, etc.

[0106] According to some embodiments, the energy management server 40 can perform the energy management function of the vehicle 10 by remotely generating and / or providing a state diagnosis, a life prediction, an operation control (e.g., cell balancing), a charging guideline, etc., of the battery 400. According to some embodiments, the energy management server 40 can execute energy management software for remotely managing the battery 400 of the vehicle 10. For example, the energy management software can transmit an instruction for performing an energy management function based on battery data provided from a battery management system (BMS) of the battery 400 to the computing system 300 or the BMS of the battery 400 of the vehicle 10. In addition, when performing the energy management function of the vehicle 10, the energy management software can additionally consider driving data provided from the communication module 100 and / or the sensor module 200.

[0107] Figure 2 FIG. 1 is a diagram illustrating a process of performing regenerative braking in a vehicle according to some embodiments disclosed herein.

[0108] Referring to Figure 2 In the vehicle 10, the computing system 300 controls the battery 400 and the drive system 500 so that discharging of the battery 400 according to driving of the vehicle 10 and charging of the battery 400 according to braking of the vehicle 10 can be performed.

[0109] According to some embodiments, the computing system 300 can control the battery 400 to supply electric power to the drive system 500. The drive system 500 can use the electric power supplied from the battery 400 to drive a motor. According to some embodiments, the drive system 500 can include one or more electric motors. When the motor is driven, the vehicle 10 can be accelerated, and even in the case of automatic cruising of the vehicle 10, the battery 400 can be discharged to drive the motor.

[0110] According to some embodiments, the computing system 300 can control the drive system 500 to charge the battery 400 when the vehicle 10 is decelerated. For example, the computing system 300 can control the drive system 500 such that a braking device of the drive system 500 operates or the motor does not generate driving force. When the motor rotates together with the wheel of the drive system 500 without receiving a separate driving force, electric power can be generated from the motor by the principle of electromagnetic induction. According to some embodiments, regenerative braking can refer to a braking method in which the battery 400 is charged using the electric power generated from the motor when the vehicle 10 is braked or decelerated.

[0111] Generally, in the case of a rechargeable secondary battery, considering that the life of the battery 400 can decrease when repeatedly charged and discharged, the battery 400 is repeatedly discharged and charged in the case of performing regenerative braking, so that the performance of the battery 400 can be deteriorated. Regenerative braking can be advantageous in terms of the driving distance of the vehicle 10 or the charging cost of the battery 400, but can be disadvantageous in terms of the performance or life of the battery 400. Accordingly, a management technique that utilizes regenerative braking of the vehicle 10 and at the same time considers deterioration of the battery 400 can be required.

[0112] Figure 3 FIG. 1 is a diagram illustrating components and functions of a battery according to some embodiments disclosed herein.

[0113] Referring to FIG. 1, Figure 3 The battery 400 can include a battery pack 410 and a battery management system 420. However, the battery 400 is not limited thereto, and some components can be omitted from the battery 400, or other general components can be added to the battery 400. According to some embodiments, the battery 400 can predict a degree of deterioration of the battery pack 410 based on driving data and battery data.

[0114] According to some embodiments, the battery management system 420 can include at least one controller or at least one processor. The at least one controller / processor of the battery management system 420 can have a structure for processing various operations, processes, and instructions. According to some embodiments, the at least one controller / processor of the battery management system 420 can be configured separately from or integrally with a memory (not shown), and can process various operations by executing instructions stored in the memory.

[0115] According to some embodiments, the battery management system 420 can predict the degree of degradation of the battery pack 410 based on the battery data measured by the battery pack 410 and the driving data measured by the communication module 100 and / or the sensor module 200 of the vehicle 10. According to some embodiments, the functions and / or operations performed by the following controller can be interpreted as being performed by the battery management system 410 in the vehicle 10.

[0116] According to some embodiments, the battery management system 420 can include a data acquirer. The data acquirer can be configured to acquire driving data related to driving of the vehicle 10 and battery data related to the battery pack 410 of the vehicle 10. For example, the data acquirer of the battery management system 420 can include an interface circuit for interacting with other components of the vehicle 10, and the communication scheme of the data acquirer can be a device-to-device communication scheme such as a bus, GPIO, SPI, MIPI.

[0117] The data acquirer of the battery management system 420 can be configured to acquire driving data related to driving of the vehicle 10 and battery data related to the battery pack 410. According to some embodiments, the driving data can include object data about objects around the vehicle 10 and movement data about movement of the vehicle 10, the object data can include the type and number of surrounding objects, the distance to the vehicle 10, the position relative to the vehicle 10, the ground position, the relative speed, the ground speed, the relative acceleration, the ground acceleration, etc., and the movement data can include the position, the movement path, the driving distance, the speed, the acceleration, the steering angle, the yaw, the pitch, the roll, etc. of the vehicle 10. According to some embodiments, the battery data can include voltage data, current data, temperature data, state of charge (SOC) data, state of health (SOH) data, and combinations thereof, and can also include cumulative charge current, cumulative discharge current, cumulative charge power, cumulative discharge power, insulation resistance, relay state, etc.

[0118] The controller of the battery management system 420 can be configured to determine whether regenerative braking of the vehicle 10 occurs based on the driving data and the battery data. According to some embodiments, it can be determined that regenerative braking occurs in a case where the SOC level of the battery pack 410 increases when the vehicle 10 decelerates. On the other hand, it can be determined that regenerative braking does not occur even if the SOC level increases in a case where the vehicle 10 is not driven or a battery charger is connected to the vehicle 10.

[0119] The controller of the battery management system 420 can be configured to derive statistical data related to the occurrence of regenerative braking. According to some embodiments, the controller can be configured to derive charging data related to charging of the battery pack 410 through regenerative braking. According to some embodiments, the statistical data can include the number of occurrences of regenerative braking, the frequency of regenerative braking, the duration of regenerative braking, and statistical variables derived therefrom. According to some embodiments, the charging data can include the amount of change in the SOC level of the battery pack 410, the amount of change in voltage, the amount of change in current, the amount of change in temperature, and battery-related variables derived therefrom.

[0120] The controller of the battery management system 420 can be configured to predict the degree of degradation of the battery pack 410 based on the statistical data. According to some embodiments, the controller can be configured to predict the degree of degradation of the battery pack 410 based on the statistical data and the charging data. According to embodiments, the degree of degradation of the battery pack 410 can include the degree of degradation due to driving of the vehicle 10 regardless of regenerative braking and the degree of degradation due to regenerative braking. According to some embodiments, the degree of degradation due to regenerative braking can increase as the number of occurrences of regenerative braking increases, the frequency of regenerative braking increases, the duration of regenerative braking increases, and the range of changes in the charging data increases, and can be expressed as a numerical value related to a degradation performance ratio based on the maximum performance of the battery pack 410.

[0121] According to some embodiments, the controller of the battery management system 420 can be configured to predict the degree of degradation based on the number of occurrences of regenerative braking according to the statistical data and the amount of charging of the battery pack 410 according to the charging data. The number of occurrences of regenerative braking can be counted based on the statistical data, and the increase in the SOC level of the battery pack 410 due to each regenerative braking can be calculated as the amount of charging. According to some embodiments, as the number of occurrences of regenerative braking increases and the amount of charging of the battery pack 410 due to regenerative braking increases, the degree of degradation can be predicted as a higher value.

[0122] According to some embodiments, the controller of the battery management system 420 can be configured to acquire whether a charger is connected to the vehicle 10 indicating whether a battery charger is connected, and determine whether regenerative braking of the vehicle 10 occurs based on the driving data, the battery data, and whether the charger is connected. According to some embodiments, in the case where the battery charger is connected, the remaining amount of the battery pack 410 can be charged even if regenerative braking is not performed, so that it can be more accurately determined whether regenerative braking occurs.

[0123] Figure 4 FIG. 1 is a diagram illustrating a vehicle according to some embodiments disclosed herein.

[0124] Referring toFigure 4 Based on the travel data of the vehicle 10 and the charge amount of the battery pack 410, the battery management system 420 can calculate an estimated level 42, can predict a degree of degradation 44 of the battery pack 410 based on the number of occurrences of regenerative braking and the estimated level 42, and can perform a charge / discharge restriction 46 of the battery pack 410 based on the degree of degradation 44.

[0125] According to some embodiments, the controller of the battery management system 420 can be configured to calculate an estimated level 42 of regenerative braking based on the travel data and the charge amount, and to predict a degree of degradation 44 based on the number of occurrences and the estimated level 42. The regenerative braking of the vehicle 10 can be performed according to a regenerative braking level. In this regard, the computing system 300 of the vehicle 10 can determine the regenerative braking level. According to some embodiments, the regenerative braking level can include 1 to 3, A to C, etc. 3 levels. In other embodiments, the regenerative braking level can include 5 levels, 8 levels, 10 levels, or any other number of levels, and in some instances, the regenerative braking level can be set to a continuous value rather than a discrete value.

[0126] The controller of the battery management system 420 can predict the value of the regenerative braking level determined by the computing system 300, or can receive the determined value of the regenerative braking level from the computing system 300. According to some embodiments, the regenerative braking level can be predicted based on the travel data and the charge amount. For example, in a case where the travel data indicates that the vehicle 10 is moderately decelerating and the charge amount indicates that the battery pack 410 is moderately charging, the estimated level 42 of regenerative braking can be predicted to be B among levels A to C.

[0127] After determining the estimated level 42 of regenerative braking, the degree of degradation 44 of the battery pack 410 can be determined according to how much regenerative braking occurs at the determined estimated level 42. According to some embodiments, the higher the estimated level 42 and the higher the number of occurrences of regenerative braking, the higher the degree of degradation 44 can be calculated. If the estimated level 42 of regenerative braking changes, the number of occurrences at the changed level can be recounted.

[0128] According to some embodiments, the controller of the battery management system 420 can also be configured to limit at least one of discharging of the battery pack 410 by travel of the vehicle 10 or charging of the battery pack 410 by regenerative braking according to a predetermined ratio based on the number of occurrences and the estimated level. According to some embodiments, the degree of degradation 44 can be calculated based on the number of occurrences and the estimated level, and the charge / discharge restriction 46 can be applied to the battery pack 410 if the degree of degradation 44 exceeds a degradation threshold.

[0129] When the charge / discharge limit 46 is applied, a part of the charge of the battery pack 410 is limited, so that only a part of the power generated by the regenerative braking is delivered to the battery pack 410, or the regenerative braking level can be set by the computing system 300 to a certain level or less. In addition, some discharges of the battery pack 410 are limited, so that the output of the drive system 500 can be reduced, and thus the speed or acceleration of the vehicle 10 can be reduced. According to the charge / discharge limit 46, over-repetition of the charge and discharge of the battery pack 410 can be prevented, and thus the degradation of the battery pack 410 can be reduced.

[0130] Figure 5 is a graph illustrating a degradation prediction model according to some embodiments disclosed herein.

[0131] Referring to Figure 5 , the controller of the battery management system 420 can predict the degree of degradation of the battery pack 410 from the charge amount and the travel data using the degradation prediction model 50, and the degradation prediction model 50 can include a first sub-model 52 and a second sub-model 54.

[0132] According to some embodiments, the controller of the battery management system 420 can be configured to predict the degree of degradation using the degradation prediction model 50, and the degradation prediction model 50 can include a first sub-model 52 trained to calculate an estimated level and a second sub-model 54 trained to predict the degree of degradation. According to some embodiments, the degradation prediction model 50 can calculate an estimated level of regenerative braking based on the travel data and the charge amount through the first sub-model 52, and can predict the degree of degradation of the battery pack 410 based on the estimated level and the number of occurrences through the second sub-model 54.

[0133] According to some embodiments, the degradation prediction model 50 can be an AI model trained and updated based on a neural network structure through various machine learning techniques. The degradation prediction model 50 can determine model parameters through machine learning with a known relationship between the charge amount, the travel data, and the degree of degradation as learning data. Then, as the travel of the vehicle 10 is accumulated, the model parameters can be continuously optimized.

[0134] According to some embodiments, the controller of the battery management system 420 can be configured to acquire a regenerative braking level of the regenerative braking determined by the computing system 300 of the vehicle 10, and compare the estimated level with the regenerative braking level to update the first sub-model 52. If the regenerative braking level actually determined by the computing system 300 can be utilized, the first sub-model 52 estimating the level of the regenerative braking can be updated. For example, in the case where a difference between the estimated level of the first sub-model 52 and the actual regenerative braking level occurs, the first sub-model 52 can be trained to reduce the difference. Accordingly, the performance of the first sub-model 52 can be improved, and even if the actual regenerative braking level is not provided later, the first sub-model 52 can provide an accurate estimated level.

[0135] According to some embodiments, the controller of the battery management system 420 can be configured to transmit the number of occurrences and the estimated level to the energy management server 40 outside the vehicle 10, and receive a predicted degree of deterioration based on the number of occurrences and the estimated level by the deterioration prediction model 50 by the energy management server 40. According to some embodiments, the deterioration prediction model 50 can be operated by the energy management server 40 rather than the battery management system 420. To this end, the battery management system 420 can provide data to be input into the deterioration prediction model 50 to the energy management server 40, and the energy management server 40 can provide the prediction result of the deterioration prediction model 50 to the battery management system 420. When the external energy management server 40 operates the deterioration prediction model 50 in this way, the model inference operation and the model update requiring a large amount of calculation can be smoothly performed.

[0136] Figure 6 FIG. 6 is a diagram illustrating operations constituting a battery management method according to some embodiments disclosed herein.

[0137] Referring to Figure 6 , the battery management method 600 can include operations 610 to 640. However, the method is not limited thereto, and some operations can be omitted or general operations can be added, and the operations of the battery management method 600 can be performed in a different order from the illustrated order.

[0138] The operations 610 to 640 in the battery management method 600 can be performed by the battery management system 420 of the battery 400. According to some embodiments, the battery management method 600 can include operations processed in time sequence in the battery management system 420. Accordingly, the above description of the battery management system 420 can be equally applied to the battery management method 600, even though the description is omitted below.

[0139] In operation 610, the battery management system 420 can acquire driving data related to driving of the vehicle and battery data related to the battery pack through the data acquirer.

[0140] In operation 620, the battery management system 420 can determine whether regenerative braking of the vehicle occurs based on the driving data and the battery data through the controller.

[0141] In operation 630, the battery management system 420 can derive statistical data related to the occurrence of regenerative braking through the controller.

[0142] In operation 640, the battery management system 420 can predict the degree of degradation of the battery pack based on the statistical data through the controller.

[0143] According to some embodiments, the battery management method 600 can be implemented in the form of a computer program stored in a computer-readable storage medium. That is, the computer program can include instructions for implementing the battery management method 600, and the instructions of the program can be stored in the computer-readable storage medium. The computer program can include a mobile application.

[0144] For example, the computer-readable medium can include a magnetic medium such as a hard disk, a floppy disk, and a magnetic tape; an optical medium such as a CD-ROM and a DVD; a magneto-optical medium such as a floptical disk; and a hardware device specially configured to store and execute program instructions such as a ROM, a RAM, a flash memory, and the like. The program instructions can include machine codes generated by a compiler and higher-level codes that can be executed by a computer using an interpreter.

[0145] Figure 7 FIG. 1 is a diagram illustrating components and functions of a computing system according to some embodiments disclosed herein.

[0146] Referring to Figure 7 , the computing system 300 can include an interface circuit 310 and at least one processor 320. However, the computing system 300 is not limited thereto, and some components can be omitted from the computing system 300, or other general-purpose components can be added to the computing system 300.

[0147] According to some embodiments, the at least one processor 320 can determine a regenerative braking level and a driving strategy of the vehicle 10 based on battery data measured by the battery pack 410, and can control driving of the vehicle 10 based on the regenerative braking level and the driving strategy. According to some embodiments, functions and / or operations performed by the at least one processor 320 below can be interpreted as being performed by the computing system 300 in the vehicle 10.

[0148] The at least one processor 320 can be configured to acquire battery data related to the battery 400 of the vehicle 10. The battery management system 420 of the battery 400 can measure the battery data from the battery pack 410 and provide the measured battery data to the computing system 300. According to some embodiments, the battery data can include voltage data, current data, temperature data, state of charge (SOC) data, state of health (SOH) data, and combinations thereof, and can also include cumulative charge current, cumulative discharge current, cumulative charge power, cumulative discharge power, insulation resistance, relay state, etc.

[0149] The at least one processor 320 can be configured to determine a regenerative braking level of the vehicle 10 based on the battery data. The regenerative braking level can refer to an operation of performing regenerative braking of the vehicle 10, and the higher the regenerative braking level, the greater the braking force of the vehicle 10 and the amount of charge of the battery 400. According to some embodiments, the regenerative braking level can include 3 levels (such as 1 to 3, A to C, etc.). In other embodiments, the regenerative braking level can include 5 levels, 8 levels, 10 levels, or any other number of levels, and in some instances, the regenerative braking level can be set to a continuous value rather than a discrete value.

[0150] The at least one processor 320 can be configured to adjust a driving strategy of the vehicle 10 based on the regenerative braking level. The driving strategy can refer to a strategy of driving the vehicle 10 considering the braking force for a given regenerative braking level. According to some embodiments, the driving strategy of the vehicle 10 can include driving speed, driving acceleration, driving route, driving responsiveness, inter-vehicle distance setting, strength of passing over bumps, etc. For example, when the regenerative braking level is relatively low, a route having a high proportion of simple driving sections can be selected, and the inter-vehicle distance that the vehicle 10 maintains with respect to a preceding vehicle can be set to be relatively long.

[0151] The at least one processor 320 can be configured to control driving of the vehicle 10 based on the regenerative braking level and the driving strategy. The drive system 500 can reduce the speed of the vehicle 10 with the braking force corresponding to the regenerative braking level, and drive the vehicle 10 according to the inter-vehicle distance setting, acceleration force, and driving route corresponding to the driving strategy. For example, in the case where the regenerative braking level is set to be relatively high, a complex path requiring a large amount of braking can be set as the driving path of the vehicle 10, and high driving responsiveness and a short inter-vehicle distance can be employed.

[0152] Since the regenerative braking level can be determined based on the battery data of the battery 400, the regenerative braking level can be limited to a low level in the case where the battery data is not required to be high level. Accordingly, degradation of the battery 400 due to unnecessary excessive regenerative braking can be prevented.

[0153] Figure 8 FIG. 1 is a diagram illustrating a process of determining a regenerative braking level and adjusting a driving strategy according to some embodiments disclosed herein.

[0154] Referring to Figure 8 , the at least one processor 320 can determine the regenerative braking levels 82 and 85 based on the SOC levels 81 and 84 of the battery 400, and can determine the driving strategies 83 and 86 based on the regenerative braking levels 82 and 85.

[0155] According to some embodiments, the battery data can include state of charge (SOC) levels 81 and 84 of the battery 400, and the at least one processor 320 can be configured to determine the regenerative braking levels 82, 85 based on a relationship inversely proportional to the SOC levels 81 and 84. According to some embodiments, the SOC levels 81 and 84 can be estimated by the battery management system 420 based on the voltage, current, and / or temperature measured from the battery pack 410 of the battery 400, or can be estimated by the at least one processor 320.

[0156] The regenerative braking levels 82 and 85 can be determined based on a relationship inversely proportional to the SOC levels 81 and 84. According to some embodiments, the SOC levels 81 and 84 can be divided into high / medium / low, and the regenerative braking levels 82 and 85 of A / B / C can be determined inversely proportional to the high / medium / low levels. Here, the inverse proportional relationship can encompass, but is not limited to, all relationships that when the SOC levels 81 and 84 increase, the regenerative braking levels 82 and 85 decrease, and when the SOC levels 81 and 84 decrease, the regenerative braking levels 82 and 85 increase. In addition, the high / medium / low SOC levels 81 and 84 and the A / B / C regenerative braking levels 82 and 85 are only examples, and other classification methods can be used.

[0157] According to some embodiments, the driving strategies 83 and 86 can be determined in various ways based on the regenerative braking levels 82 and 85. First, in the case where the battery 400 is prioritized, when the regenerative braking levels 82 and 85 are set to high, the driving strategies 83 and 86 can be set in the direction of reducing the discharge amount of the battery 400. On the contrary, in the case where the driving of the vehicle 10 is prioritized, when the regenerative braking levels 82 and 85 are set to high, the driving strategies 83 and 86 can be set to a sport mode or the like that can utilize high braking force. On the other hand, as for the driving performance of the vehicle 10 and the efficiency of the battery 400, the driving strategies 83 and 86 are divided into performance / normal / economic strategies, but different division operations and division criteria can be used to the extent that the regenerative braking levels 82 and 85 are considered.

[0158] According to some embodiments, in a case where the regenerative braking level is increased to utilize an increase in braking force, the at least one processor 320 can adjust the travel strategy in consideration of the increase in braking force of the vehicle 10. For example, when the regenerative braking level is increased, as the increased braking level provides more braking power to the vehicle, the travel speed can increase and / or the inter-vehicle distance can decrease. Thus, the vehicle can stop faster than when the braking level is at a lower level. The at least one processor 320 can adjust the travel strategy in consideration of a decrease in braking force of the vehicle 10 in a case where the regenerative braking level is decreased to address the decrease in braking force. For example, when the regenerative braking level is set to a lower level, as the decreased braking level decreases the braking power available to the vehicle, the travel speed can decrease and / or the inter-vehicle distance can increase. Thus, the vehicle can slow down to a stop more slowly than when the braking level is set to a higher level.

[0159] According to some embodiments, the at least one processor 320 can be configured to adjust the travel strategy by changing at least one of the travel speed, the travel route, the travel responsiveness, and the inter-vehicle distance setting of the vehicle 10 according to an increase or decrease in the regenerative braking level. For example, in a case where the travel strategy is Eco, the travel speed is decreased, the travel route is set to a simple route that requires less braking, the travel responsiveness is set to low to reduce repetition of acceleration and deceleration, and the inter-vehicle distance is set to long due to low braking force.

[0160] According to some embodiments, the at least one processor 320 can be configured to calculate a discharge amount of the SOC level according to travel of the vehicle 10 and to calculate a charge amount of the SOC level according to regenerative braking of the vehicle 10, and to determine the regenerative braking level based on the discharge amount and the charge amount. Since the battery 400 repeatedly charges due to deceleration of the vehicle 10 and discharges due to acceleration of the vehicle 10, it can be necessary to consider both the charge amount and the discharge amount. According to some embodiments, the charge amount and the discharge amount of the SOC level can be calculated for a certain time such as 5 minutes, 3 minutes, 2 minutes, 1 minute, 30 seconds, 20 seconds, 15 seconds, 10 seconds, 5 seconds, etc., and the regenerative braking level can be determined based on the calculated charge amount and discharge amount. For example, the regenerative braking level can be determined by comparing a ratio of the charge amount to the discharge amount for the certain time to a threshold ratio.

[0161] According to some embodiments, at least one processor 320 can be configured to calculate, based on the discharge and charge amounts, a predicted discharge and charge amount at a State of Charge (SOC) level after a predetermined time, determine the next level of regenerative braking based on the predicted discharge and charge amounts, and maintain the next level until the predetermined time has elapsed. For example, the charge and discharge amounts for specific time periods such as 5 minutes, 3 minutes, 2 minutes, 1 minute, 30 seconds, etc., can be calculated, and the predicted discharge and charge amounts at the SOC level after the predetermined time can be calculated based on this calculation. According to some embodiments, the predetermined time can be 5 minutes, 3 minutes, 2 minutes, 1 minute, 30 seconds, 20 seconds, 15 seconds, 10 seconds, 5 seconds, etc. For example, the predicted discharge amount after a predetermined time of 5 minutes can be set to be equal to the discharge amount during the specific time period of 5 minutes. According to some embodiments, when calculating the predicted discharge and charge amounts, the GPS location of the vehicle 10, navigation driving information, etc., can be additionally considered.

[0162] The next level of regenerative braking can be determined based on the predicted discharge and charge amounts. The next level can be set equal to, greater than, or less than the previous regenerative braking level. For example, when the predicted discharge is greater than the current discharge and the predicted charge is less than the current charge, the next level can be set higher than the previous regenerative braking level to offset the decrease in the battery's SOC level. After setting the next level, the set level can be maintained for a predetermined time.

[0163] According to some implementations, the predicted discharge and charge amounts can be predicted based on a SOC-level prediction model. The SOC-level prediction model can be an AI model trained and updated using various machine learning techniques based on neural network structures, and its parameters can be updated by comparing the predicted discharge and charge amounts with the actual measured discharge and charge amounts. According to some implementations, the SOC-level prediction model can be managed by an energy management server 40 instead of at least one processor 320.

[0164] Figure 9 This is a diagram illustrating a process of adjusting only the driving strategy while maintaining the regenerative braking level, according to some embodiments disclosed herein.

[0165] refer to Figure 9 Even if a SOC level change occurs (910), at least one processor (320) will not change the regenerative braking level as it would in regenerative braking level maintenance (920), but will instead adjust the driving strategy as it would in driving strategy adjustment (930). In this way, the regenerative braking level can be prevented from being set high, allowing regenerative braking to reduce battery degradation (400).

[0166] According to some embodiments, the at least one processor 320 can be configured to maintain the same regenerative braking level in response to a change in the battery data, and to adjust the travel strategy considering a difference in the battery charge amount due to maintaining the regenerative braking level. For example, even if the battery data fluctuates as in the SOC level change 910, the regenerative braking level can be maintained and only the travel strategy can be controlled. According to this method, it is possible to prevent a change in the regenerative braking level from affecting the lifespan of the battery 400.

[0167] According to some embodiments, the at least one processor 320 can be configured to determine whether an increase in the regenerative braking level is required in the next period based on a change in the battery data in the current period, determine the regenerative braking level in the next period as in the current period in the case where it is determined that an increase is required, and adjust the travel strategy in the next period by reflecting an amount of reduction in the battery charge amount due to maintaining the regenerative braking level.

[0168] According to some embodiments, the current period and the next period can have values such as 1 second, 3 seconds, 5 seconds, 10 seconds, 15 seconds, 20 seconds, 30 seconds, 1 minute, 2 minutes, 3 minutes, 5 minutes, 10 minutes, etc. Depending on the battery data that changes in the current period, an increase in the regenerative braking level can or can not be required. For example, when the output voltage, the output current, and the SOC level of the battery 400 decrease in the current period, it can be determined that an increase in the regenerative braking level is required. Although an increase in the regenerative braking level is required, the regenerative braking level in the next period can be the same as the regenerative braking level in the current period. Since the regenerative braking level is not increased, the battery charge amount can be reduced, and the travel strategy in the next period can be adjusted to compensate for the amount of reduction in the battery charge amount. For example, to compensate for the amount of reduction in the battery charge amount, the travel responsiveness can be lowered, the inter-vehicle distance can be set to increase, and the travel route can be changed to a route having a high automatic cruise speed. In this way, since an increase in the regenerative braking level can be prevented, it is possible to reduce the degradation of the battery 400 due to regenerative braking.

[0169] Figure 10 FIG. 1 is a diagram illustrating operations constituting a method for operating a computing system according to some embodiments disclosed herein.

[0170] Referring to Figure 10 The operation method 1000 for operating the computing system 300 can include operations 1010 to 1040. However, the method is not limited thereto, and some operations can be omitted or general operations can be added, and the operations of the operation method 1000 can be performed in a different order from the illustrated order.

[0171] Operations 1010 to 1040 of the operation method 1000 of the computing system 300 can be performed by the computing system 300 of the vehicle 10. According to some embodiments, the operation method 1000 can include operations processed in chronological order by the computing system 300. Accordingly, the above description of the computing system 300 can be equally applied to the operation method 1000, even though the description is omitted below.

[0172] In operation 1010, the computing system 300 can acquire battery data related to a battery of the vehicle.

[0173] In operation 1020, the computing system 300 can determine a regenerative braking level of the vehicle based on the battery data.

[0174] In operation 1030, the computing system 300 can adjust a driving strategy of the vehicle based on the regenerative braking level.

[0175] In operation 1040, the computing system 300 can control driving of the vehicle based on the regenerative braking level and the driving strategy.

[0176] According to some embodiments, the operation method 1000 of the computing system 300 can be implemented in the form of a computer program stored in a computer-readable storage medium. That is, the computer program can include instructions for implementing the operation method 1000, and the instructions of the program can be stored in the computer-readable storage medium. The computer program can include a mobile application.

[0177] For example, the computer-readable medium can include magnetic media such as a hard disk, a floppy disk, and a magnetic tape; optical media such as a CD-ROM and a DVD; magneto-optical media such as a floptical disk; and hardware devices specifically configured to store and execute program instructions such as a ROM, a RAM, a flash memory, and the like. The program instructions can include machine codes generated by a compiler and higher level codes that can be executed by a computer using an interpreter.

[0178] Unless otherwise specified, the above terms such as "include," "comprise," or "have" mean that the corresponding element can be embedded therein, and thus it means that other elements can be further included rather than excluding other elements. Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as those commonly understood by one of ordinary skill in the art to which this disclosure belongs.

[0179] Although exemplary embodiments of the present disclosure have been described for illustrative purposes, those skilled in the art will appreciate that various changes and modifications are possible without departing from the scope and spirit of the present disclosure. Therefore, the embodiments disclosed in the present disclosure are provided for description, not to limit the technical idea of the present disclosure, and it should be understood that the embodiments are not intended to limit the scope of the technical idea of the present disclosure. The scope of protection of the present disclosure should be understood by the claims below, and all technical ideas within the equivalent scope should be interpreted as being within the scope of the rights of the present disclosure.

[0180] [Reference Signs]

[0181] 1: vehicle management system 10: vehicle

[0182] 20: network 30: autonomous travel management server

[0183] 40: energy management server 100: communication module

[0184] 200: sensor module 300: computing system

[0185] 310: interface circuit 320: at least one processor

[0186] 400: battery 410: battery pack

[0187] 420: battery management system 500: drive system

Claims

1. A computing system comprising: At least one processor, said at least one processor being configured to: Receive battery data related to the vehicle's battery; The regenerative braking level of the vehicle is determined based on the battery data; The vehicle's driving strategy is adjusted based on the regenerative braking level. as well as The vehicle's movement is controlled based on the driving strategy.

2. The computing system according to claim 1, wherein, The battery data includes the battery's state of charge (SOC) level, and the at least one processor is further configured to: The regenerative braking level is determined based on a relationship inversely proportional to the SOC level.

3. The computing system according to claim 2, wherein, The at least one processor is further configured to: The discharge amount at the SOC level is calculated based on the vehicle's driving data, and the charging amount at the SOC level is calculated based on the vehicle's regenerative braking data. The regenerative braking level is determined based on the discharge amount and the charge amount.

4. The computing system according to claim 3, wherein, The at least one processor is further configured to: After a predetermined time has elapsed, the predicted discharge and predicted charge levels at the SOC level are calculated, wherein the calculation of the predicted discharge and predicted charge levels is based on the discharge and charge levels; and The next level of the regenerative braking level is determined based on the predicted discharge amount and the predicted charge amount.

5. The computing system according to claim 1, wherein, Adjusting the vehicle's driving strategy based on the regenerative braking level includes adjusting one or more of the vehicle's driving speed, driving route, driving responsiveness, or inter-vehicle distance settings.

6. The computing system according to claim 5, wherein, Adjusting the vehicle's driving strategy based on the regenerative braking level includes: increasing the vehicle's driving speed and / or decreasing the inter-vehicle distance setting when the regenerative braking level increases.

7. The computing system according to claim 5, wherein, Adjusting the vehicle's driving strategy based on the regenerative braking level includes: increasing the driving responsiveness and / or setting the driving route to require more braking from the vehicle when the regenerative braking level increases.

8. The computing system according to claim 5, wherein, Adjusting the vehicle's driving strategy based on the regenerative braking level includes: reducing the vehicle's driving speed and / or increasing the inter-vehicle distance setting when the regenerative braking level decreases.

9. The computing system according to claim 5, wherein, Adjusting the vehicle's driving strategy based on the regenerative braking level includes: reducing the driving responsiveness to decrease acceleration and / or braking events when the regenerative braking level is reduced; and / or setting the driving route to a route that requires less braking from the vehicle.

10. The computing system according to claim 1, wherein, The at least one processor is further configured to: In response to changes in the battery data, maintain the same regenerative braking level; and The driving strategy is adjusted based on the difference in battery charge caused by maintaining the regenerative braking level.

11. The computing system according to claim 10, wherein, The at least one processor is further configured to: Based on the changes in the battery data during the current period, determine whether the regenerative braking level needs to be increased in the next period. If it is determined that an increase is needed, the regenerative braking level in the next time period shall be determined in the same manner as in the current time period; as well as The driving strategy in the next time period is adjusted by reflecting the amount of reduction in battery charge due to maintaining the regenerative braking level.

12. A vehicle comprising: Battery; as well as The computing system according to claim 1.

13. A vehicle control method, the vehicle control method comprising the following steps: Battery data related to the vehicle's battery is received by one or more processors; The regenerative braking level of the vehicle is determined by one or more processors based on the battery data; The vehicle's driving strategy is adjusted by one or more processors based on the regenerative braking level; as well as The driving of the vehicle is controlled by one or more processors based on the driving strategy.

14. The vehicle control method according to claim 13, wherein, The battery data includes the battery's State of Charge (SOC) level, and The step of determining the regenerative braking level includes determining the regenerative braking level based on a relationship inversely proportional to the SOC level.

15. The vehicle control method according to claim 14, wherein, The steps for determining the regenerative braking level include: The discharge amount at the SOC level is calculated based on the vehicle's driving, and the charging amount at the SOC level is calculated based on the vehicle's regenerative braking, wherein the regenerative braking level is determined based on the discharge amount and the charging amount.

16. The vehicle control method according to claim 13, wherein, The step of determining the regenerative braking level includes: maintaining the same regenerative braking level in response to changes in the battery data, and The step of adjusting the driving strategy includes: taking into account the difference in battery charge caused by maintaining the regenerative braking level to adjust the driving strategy.

17. The vehicle control method according to claim 13, wherein, The step of adjusting the vehicle's driving strategy based on the regenerative braking level includes adjusting one or more of the vehicle's driving speed, driving route, driving responsiveness, or inter-vehicle distance settings.

18. The vehicle control method according to claim 17, wherein, The step of adjusting the vehicle's driving strategy based on the regenerative braking level includes: increasing the vehicle's driving speed and decreasing the inter-vehicle distance setting when the regenerative braking level increases; increasing the driving responsiveness; and / or setting the driving route to a route that requires more braking from the vehicle.

19. The vehicle control method according to claim 17, wherein, The step of adjusting the vehicle's driving strategy based on the regenerative braking level includes: when the regenerative braking level is reduced, reducing the vehicle's driving speed, increasing the inter-vehicle distance setting, reducing the driving responsiveness to reduce acceleration events and / or braking events, and / or setting the driving route to a route that requires less braking from the vehicle.

20. A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform the following operations: Obtain battery data related to the vehicle's battery; The regenerative braking level of the vehicle is determined based on the battery data; The vehicle's driving strategy is adjusted based on the regenerative braking level. as well as The vehicle's movement is controlled based on the driving strategy.

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