Vehicles, computing systems, methods of operating computing systems, and computer programs

Abstract

The vehicle may include a battery and a computing system configured to analyze a first calculation relating to the vehicle's driving control and a second calculation relating to the vehicle's energy management, acquire battery state information relating to the battery, and manage the processing of the first and second calculations based on the battery state information.

Description

Technical Field

[0001] This application claims the benefit of priority based on Korean Patent Application No. 10-2023-0152137 filed on November 6, 2023, Korean Patent Application No. 10-2023-0132069 filed on October 4, 2023, and Korean Patent Application No. 10-2023-0056681 filed on April 28, 2023, and all the contents disclosed in the documents of the Korean patent applications are incorporated herein by reference.

[0002] The embodiments disclosed in this document relate to vehicles, computing systems, methods for operating a computing system, and computer programs.

Background Art

[0003] As the demand for environmentally friendly vehicles increases, electric vehicles (EVs) using batteries such as lithium-ion secondary batteries as an energy source are rapidly replacing conventional internal combustion engine vehicles. On the other hand, with the advancement of artificial intelligence technology and various sensor technologies, research and development for improving the performance of hardware and software related to the autonomous driving system of vehicles are also actively underway. Along with this, in recent years, an autonomous driving system for assisting the autonomous driving of vehicles has been developed or provided in the form of a single autonomous driving platform including various sensors and a control unit, and some electric vehicle manufacturers are mass-producing or developing autonomous driving electric vehicles based on the autonomous driving platform.

[0004] To reduce or eliminate greenhouse gas emissions and thereby mitigate the effects of climate change, vehicle energy management is crucial for further advancing autonomous driving technology in electric vehicles. In this regard, various behaviors and events that determine driving scenarios can occur while a vehicle is autonomously driving. Such events are inevitably closely related to energy consumption or energy management. However, typical electric vehicles either lack energy management functions or do not consider energy management except for calculations related to such energy management functions that are generally handled by a battery management system (BMS) built into the battery itself. However, as the diversification of energy management functions increases, more advanced energy management calculations are required, which can lead to problems where the processing capacity of the BMS reaches its limits. [Overview of the project] [Problems that the invention aims to solve]

[0005] The aspects of this disclosure are intended to at least resolve the problems and / or disadvantages mentioned herein and to provide at least the advantages described herein. Accordingly, the aspects of this disclosure are intended to provide a vehicle, a computing system and its operating method, and a computer program that can efficiently handle calculations relating to vehicle driving control and / or energy management functions. Energy management functions enable more economical driving by the autonomous driving platform compared to conventional autonomous vehicles. This can sequentially further improve the overall energy efficiency of the vehicle, which can lead to a reduction in energy use. Furthermore, energy management functions can be implemented in various types of automated vehicle platforms, which can lead to widespread improvements in energy efficiency.

[0006] The technical objectives of the embodiments disclosed herein are not limited to the technical problems mentioned above, and any other technical problems not mentioned can be clearly understood by those skilled in the art from the following description. [Means for solving the problem]

[0007] According to one aspect of this disclosure, an autonomous driving platform includes at least one processor operationally coupled to a vehicle's battery, the at least one processor having computing resources configured to perform at least a first operation relating to the vehicle's driving control and a second operation relating to the vehicle's energy management, the at least one processor being configured to obtain battery state information relating to the vehicle's battery from the battery and to manage the allocation of computing resources for performing the first operation and computing resources for performing the second operation, at least in part based on the battery state information.

[0008] According to some embodiments, the allocation of computing resources is based on the processing priority between the first and second operations, and the processing priority between the first and second operations is based on the battery status information.

[0009] According to some embodiments, the battery state information includes battery temperature information, and the at least one processor is configured to determine the processing priority such that the first operation has priority over the second operation in response to an indication that the battery is not overheating based on the battery temperature information, and to determine the processing priority such that the first operation and the second operation have equal priority to each other in response to an indication that the battery is overheating based on the battery temperature information.

[0010] According to some embodiments, the processing priority is based on the amount of battery state information received during a predetermined time interval and the amount of processing of the second calculation during the predetermined time interval.

[0011] According to some embodiments, the at least one processor is configured to set the processing priority so that the first operation takes precedence over the second operation in response to the amount of battery state information received that exceeds a critical amount.

[0012] According to some embodiments, the at least one processor is configured to set the processing priority so that the first operation takes precedence over the second operation in response to the amount of battery state information received that does not exceed a critical amount.

[0013] According to some embodiments, the at least one processor is configured to acquire driving information relating to the driving of the vehicle, determine the occurrence of a driving priority event relating to driving control based on the driving information, and, in response to the driving priority event, determine the processing priority of the first and second operations based on the driving priority event.

[0014] According to some embodiments, the driving priority event is one of the following weather-related events that require increased steering control, increased acceleration / deceleration control, or increased computation.

[0015] According to some embodiments, the allocation of computing resources includes determining a ratio of the computing priority of the second operation to the first operation based on the battery state information, wherein the computing priority ratio allocates individual portions of the computing resources to the first and second operations, respectively.

[0016] According to some embodiments, the at least one processor acquires battery state information relating to the vehicle's battery, determines the occurrence of a driving priority event relating to driving control based on the driving information, and in response to the driving priority event, sets the calculation priority ratio value to an upper priority ratio value that gives priority to the second calculation over the first calculation by a predetermined maximum amount.

[0017] According to some embodiments, the at least one processor is configured to assign at least a portion of the second operation to the battery management system of the battery in response to the operation priority ratio value which is equal to or greater than the priority ratio reference value, and to process the second operation based on the partial second operation result received from the battery management system.

[0018] According to some embodiments, the autonomous driving platform further includes the battery, the battery includes the battery management system, the battery management system is configured to perform at least a portion of the second calculation and to transmit the partial second calculation result to the at least one processor.

[0019] According to some embodiments, the battery management system is operated remotely in part such that at least a portion of the partial second calculation result is received from a remote portion of the battery management system.

[0020] According to some embodiments, the first and second operations are performed in parallel.

[0021] According to some embodiments, the allocation of the computing resources includes determining the order of the first and second operations based on the battery state information, the order determining which of the first and second operations the computing resources will perform first.

[0022] According to some embodiments, the at least one processor and the computing resources are included in a system-on-chip.

[0023] According to some embodiments, the system-on-chip includes only one processing chip.

[0024] According to some embodiments, the autonomous driving platform further includes an interface circuit configured to operatively connect the at least one processor to one or more of the vehicle's sensors.

[0025] According to some embodiments, the at least one processor is included in the vehicle.

[0026] According to some embodiments, the computing resources are included in the vehicle.

[0027] According to some embodiments disclosed in this document, a method for operating a computing system includes utilizing computing resources to perform at least a first operation related to vehicle driving control and a second operation related to energy management of the vehicle, obtaining battery state information regarding the vehicle's battery from a battery, and managing an allocation of computing resources for performing the first operation and computing resources for performing the second operation based at least in part on the battery state information.

[0028] According to some embodiments, the allocation of the computing resources can be based on a processing priority order between the first operation and the second operation based on the battery state information.

[0029] According to some embodiments, the battery state information can include battery temperature information. Determining the processing priority order includes determining the processing priority order such that the first operation has a priority over the second operation in response to an indication that the battery based on the battery temperature information is not overheating, and determining the processing priority order such that the first operation and the second operation have equal priority with respect to each other in response to an indication that the battery based on the battery temperature information is overheating.

[0030] According to some embodiments, the determination of the processing priority order can be based on a received amount during a predetermined time period of the battery state information and a processed amount during the predetermined time period of the second operation.

[0031] According to some embodiments, the management of the processing includes determining an occurrence of a driving priority event related to driving control based on the driving information, processing an operation corresponding to the driving priority event, and determining the processing priority order of the first operation and the second operation based on the driving priority event in response to the driving priority event.

[0032] According to some embodiments, the allocation of computing resources includes the step of determining the ratio of the computing priority of the second operation to the first operation based on the battery state information, wherein the ratio of computing priority allocates individual portions of the computing resources to the first and second operations, respectively.

[0033] According to some embodiments, the calculation of the calculation priority ratio value may include the steps of: acquiring battery state information relating to the vehicle's battery; determining the occurrence of a driving priority event relating to driving control based on the driving information; and, in response to the driving priority event, setting the calculation priority ratio value to an upper priority ratio value that gives the second calculation priority to the first calculation by a predetermined maximum amount.

[0034] According to some embodiments, the step of managing the process may include assigning at least a portion of the second calculation to the battery management system of the battery in response to the calculation priority ratio value which is equal to or greater than a priority ratio reference value, and processing the second calculation based on the partial second calculation result received from the battery management system.

[0035] According to some embodiments disclosed herein, when a computer program instruction stored on a computer-readable medium is executed by at least one processor, the at least one processor performs the following steps: utilizes computing resources to perform at least a first operation relating to vehicle driving control and a second operation relating to vehicle energy management; obtains battery state information relating to the vehicle's battery from a battery; and manages the allocation of computing resources for performing the first operation and computing resources for performing the second operation, at least in part, based on the battery state information.

[0036] According to some embodiments, the allocation of computing resources can be based on the processing priority between the first and second operations based on the battery status information.

[0037] According to some embodiments, the battery state information may include battery temperature information. The determination of the processing priority may include the steps of determining the processing priority in response to an indication that the battery is not overheating based on the battery temperature information, such that the first operation has priority over the second operation, and determining the processing priority in response to an indication that the battery is overheating based on the battery temperature information, such that the first operation and the second operation have equal priority over each other.

[0038] According to some embodiments, the determination of the processing priority can be based on the amount of battery state information received during a predetermined time interval and the amount of processing of the second calculation during the predetermined time interval.

[0039] According to some embodiments, the management of the process may include the steps of: determining the occurrence of a driving priority event related to driving control based on the driving information; processing a calculation corresponding to the driving priority event; and determining the processing priority of the first and second calculations based on the driving priority event in response to the driving priority event.

[0040] According to some embodiments, the allocation of computing resources includes the step of determining the ratio of the computing priority of the second operation to the first operation based on the battery state information, wherein the ratio of computing priority allocates individual portions of the computing resources to the first and second operations, respectively.

[0041] According to some embodiments, the calculation of the calculation priority ratio value may include the steps of: acquiring battery state information relating to the vehicle's battery; determining the occurrence of a driving priority event relating to driving control based on the driving information; and, in response to the driving priority event, setting the calculation priority ratio value to an upper priority ratio value that gives the second calculation priority to the first calculation by a predetermined maximum amount.

[0042] According to some embodiments, the step of managing the process may include assigning at least a portion of the second calculation to the battery management system of the battery in response to the calculation priority ratio value which is equal to or greater than a priority ratio reference value, and processing the second calculation based on the partial second calculation result received from the battery management system.

[0043] According to other aspects of this disclosure, the vehicle includes a battery and an autonomous driving platform as described in any of these embodiments. [Effects of the Invention]

[0044] According to the embodiments disclosed herein, it is possible to provide a vehicle, a computing system, a method of operating the same, and a computer program that can efficiently process calculations related to vehicle driving control and / or energy management functions.

[0045] According to the embodiments disclosed herein, the vehicle's computing system can efficiently process calculations related to vehicle driving control and battery energy management. Therefore, the vehicle's energy can be managed more efficiently.

[0046] The technical effects of the embodiments disclosed herein are not limited to those mentioned above, and any further effects not mentioned herein can be clearly understood by those skilled in the art through the disclosures herein. [Brief explanation of the drawing]

[0047] [Figure 1] This is a diagram illustrating a vehicle management system according to some embodiments disclosed in this document. [Figure 2] This figure illustrates the process by which driving control and energy management are performed in a vehicle according to some embodiments disclosed in this document. [Figure 3] This figure illustrates a first computing system according to some embodiments disclosed in this document. [Figure 4] This figure illustrates the process by which processing priorities are determined in a first computing system according to some embodiments disclosed in this document. [Figure 5] This figure illustrates the process by which processing priority is calculated in a first computing system according to some embodiments disclosed in this document. [Figure 6] This figure illustrates the steps that constitute the operation method of the first computing system according to some embodiments disclosed in this document. [Figure 7] This figure illustrates a second computing system according to some embodiments disclosed in this document. [Figure 8] This figure illustrates a method by which battery status information is utilized in a second computing system according to some embodiments disclosed in this document. [Figure 9] This figure illustrates the process by which processing priority is calculated in a second computing system according to some embodiments disclosed in this document. [Figure 10] This figure illustrates the steps that constitute the operation method of a second computing system according to some embodiments disclosed in this document. [Figure 11] This figure illustrates a third computing system according to some embodiments disclosed in this document. [Figure 12]This figure illustrates a method for calculating the ratio of the first and second operations in a third computing system according to some embodiments disclosed in this document. [Figure 13] This figure illustrates the steps that constitute the operation method of a third computing system according to some embodiments disclosed in this document. [Modes for carrying out the invention]

[0048] The embodiments described herein are described below with reference to the attached drawings. However, this should not be understood as limiting the disclosures herein to any particular embodiment, but rather as including various modifications, equivalents, and / or alternatives to the embodiments described herein.

[0049] The embodiments and terminology used in this document should be understood to include a variety of modifications, equivalents, or substitutions of the embodiments, rather than limiting the technical features described herein to any particular embodiment. In relation to the description of the drawings, similar or related components are referred to by similar reference numerals. The singular form of a noun corresponding to an item may include one or more such items unless the context clearly indicates otherwise.

[0050] In this document, each of the phrases “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” may include any one of the items listed with the phrase in question, or any possible combination thereof. Terms such as “first,” “second,” “first,” “second,” “A,” “B,” “(a),” or “(b)” are used solely to distinguish one component from other components and, unless otherwise stated, do not limit the component in any other way (e.g., weight or order).

[0051] Wherever a component (e.g., the first) is referred to as being "coupled," "joined," or "connected" to another component (e.g., the second) with or without such terms, it means that the first component may be connected to the other component directly (e.g., by wire or wirelessly) or indirectly (e.g., via the third component).

[0052] The methods according to the various embodiments disclosed herein may be provided in a computer program product. A computer program product may be traded as a commodity between a seller and a buyer. A computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory, CD-ROM) or online (e.g., download or upload) via an application store or directly between two user devices. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or generated on an ad-hoc basis in a device-readable storage medium such as the memory of a manufacturer's server, an application store server, or an intermediary server.

[0053] According to the embodiments disclosed herein, each of the aforementioned components (e.g., a module or a program) may include one or more individuals, and some of the individuals may be separated and arranged in other components. According to the embodiments disclosed herein, one or more of the aforementioned components or operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., a module or a program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the components of the multiple components before the integration. According to the embodiments disclosed herein, operations performed by a module, program, or other component may be performed sequentially, in parallel, repeatedly, or heuristically, or one or more of the operations may be performed in a different order, omitted, or one or more other operations may be added.

[0054] Figure 1 is a diagram illustrating a vehicle management system according to some embodiments disclosed in this document.

[0055] Referring to Figure 1, the vehicle management system 1 may include a vehicle 10, a network 20, and a data management server 30. For example, the vehicle management system 1 may mean a system in which the data management server 30 analyzes and / or manages data about the vehicle 10 collected via the network 20.

[0056] Vehicle 10 may include a communication module 100, a sensor module 200, a computing system 300, a battery 400, and a drive system 500. For example, vehicle 10 may be an electric vehicle (EV) or a hybrid electric vehicle (HEV) that generates driving force using electrical energy. Furthermore, according to various embodiments, vehicle 10 may include a vehicle with autonomous driving capabilities, and the communication module 100, sensor module 200, and computing system 300 may be implemented in the form of an autonomous driving platform, but are not limited thereto.

[0057] The communication module 100 can send and receive data with external components of the vehicle 10. For example, the communication module 100 can establish wired and / or wireless communication channels with the network 20 and exchange various data with external components of the vehicle via the established communication channels. In particular, the communication module 100 can access external devices of the vehicle 10, such as processing and data storage devices included in or connected to the network 20, via the network 20. For example, the processing and data storage devices may include one or more servers, such as a server that communicates with the autonomous driving platform, a server that communicates with the vehicle's battery, other servers, or a combination thereof.

[0058] The sensor module 200 can detect the position of objects located around the vehicle 10 and the vehicle itself. For example, the sensor module 200 may include a camera sensor for detecting surrounding objects, a GNSS (Global Navigation Satellite System) sensor to assist with mapping, recognition, occupancy grid generation, and / or path planning functions, a RADAR sensor for detecting surrounding 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 IMU (Inertial Measurement Unit) sensor including an accelerometer, magnetometer, gyroscope, and / or magnetic compass, a vibration sensor, a temperature sensor, and / or speed sensor.

[0059] The computing system 300 can manage the operation of the vehicle 10 and the overall functions that the vehicle 10 provides, including but not limited to autonomous driving functions and energy management functions. 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.

[0060] The computing system 300 can process a variety of calculations related to the vehicle 10 and can execute programs, software, or instructions. According to some embodiments, the computing system 300 can process calculations related to the driving control of the vehicle 10 and / or calculations related to energy management functions. For example, calculations related to the driving control of the vehicle 10 may include calculations for determining / deciding the driving strategy, driving path, behavior, etc., of the vehicle 10.

[0061] The computing system 300 can process calculations related to the driving control of the vehicle 10 and / or calculations related to energy management functions based on the driving information of the vehicle 10 and / or the status information of the battery 400. According to some embodiments, the computing system 300 can process calculations related to the driving control of the vehicle 10 and calculations related to energy management functions, respectively, according to the processing priority of calculations related to the driving control of the vehicle 10 and calculations related to energy management functions, which are determined based on the driving information of the vehicle 10 and / or the status information of the battery 400. This allows the computing system 300 to process a variety of calculations in a timely and efficient manner according to the driving conditions of the vehicle 10. This will be explained in more detail below.

[0062] The computing system 300 may include at least one processor for arithmetic processing and instruction execution, and interface circuits for interacting with other elements of the vehicle 10. According to some embodiments, the communication method of the interface circuit can be an inter-device communication method such as a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface).

[0063] At least one processor of the computing system 300 may have a structure for executing instructions that realize processes to be processed inside the vehicle 10. At least one processor may be implemented as an array of numerous logic gates for processing a variety of operations, or as a general-purpose microprocessor, and may consist of a single processor or multiple processors. For example, at least one processor may be implemented as a microprocessor, CPU, GPU, AP, or a combination thereof.

[0064] At least one processor of the computing system 300 is configured separately from or integrated with memory (not shown) configured to store instruction words, and can execute the instruction words stored in memory to perform various operations. The memory can store various data, instruction words, mobile applications, computer programs, etc. For example, the memory can be implemented as non-volatile memory such as ROM, PROM, EPROM, EEPROM, flash memory (registered trademark), PRAM, MRAM, RRAM (registered trademark), FRAM (registered trademark), or volatile memory such as DRAM, SRAM, SDRAM, PRAM, RRAM, FeRAM, and can be implemented in the form of HDD, SSD, SD, Micro-SD, or a combination thereof.

[0065] The battery 400 can supply power and / or electrical energy to the vehicle 10. For example, the battery 400 is a rechargeable secondary battery that is discharged while supplying power to the vehicle 10 and charged by a battery charger, and may, but is not limited to, a lithium-ion battery. According to some embodiments, the battery 400 may include battery cells, battery modules, battery packs, and / or battery racks, and may include a battery management system (BMS) for managing the battery cells, modules, packs, etc.

[0066] The battery management system (BMS) can manage the overall operation / function of the battery 400. According to some embodiments, the battery management system (BMS) can process calculations related to energy management functions, and optionally, the battery management system (BMS) can provide the results of these calculations to a computing system 300. The BMS can be part of the vehicle. In some examples, the BMS can be located entirely inside the vehicle, such as being contained within the battery 400. In other examples, the BMS can be located entirely or partially remotely from the vehicle. For example, the battery management functions of the BMS can be handled by a distributed computing network or cloud network of computing resources.

[0067] The drive system 500 can control the driving and / or behavior of the vehicle 10. For example, it can control the operation of actuators related to braking, driving, and positioning of the vehicle 10. According to some embodiments, the drive system 500 may include, but is not limited to, a braking system that controls the operation of actuators related to braking, a position control system that controls the operation of actuators for maintaining a stable position of the vehicle body, a steering system that controls the operation of actuators that control the lateral behavior of the vehicle, a transmission system that controls the operation of actuators for automatic transmission, and / or an engine management system that controls the operation of actuators that control the vehicle's speed.

[0068] According to some embodiments, the drive system 500 can control the driving and / or behavior of the vehicle 10 in response to control commands from the computing system 300. For example, the drive system 500 can control the driving and / or behavior of the vehicle 10 in response to control commands based on calculation results from the computing system 300 (e.g., calculation / execution results of autonomous driving software).

[0069] Network 20 may mean a data communication network that facilitates communication between the vehicle 10 and the data management server 30. For example, network 20 may include, but is not limited to, a wired network, a wireless network, or a combination thereof, and may be any other type of network as long as it facilitates data exchange. According to some embodiments, a wired network may include a short-range or wide-area internet that supports the TCP / IP protocol, and a wireless network may include a base station-based wireless communication network, a satellite communication network, a short-range wireless communication network such as Wi-Fi, or a combination thereof.

[0070] According to some embodiments, network 20 may include cellular networks such as 2G to 5G networks and future network generations, LTE networks, GSM® (Global System for Mobile Communication) networks, CDMA (Code Division Multiple Accesses) networks, EVDO (Evolution-Data Optimization) networks, Public Land Mobile networks, and / or other networks. According to some embodiments, network 20 may include local area networks (LANs), wireless local area networks (WLANs), wide area networks, metropolitan networks (MANs), public switched telephone networks (PSTNs), ad hoc networks, managed IP networks, virtual private networks, intranets, the internet, fiber optic infrastructure networks, and / or combinations thereof, or other types of networks.

[0071] According to various embodiments, the data management server 30 may include a communication module, a processor, a database, etc. The data management server 30 can acquire vehicle information from the vehicle 10 via the communication module. For example, the vehicle information may include driving information regarding the vehicle 10's movement and / or battery status information regarding the state of the battery 400. The data management server 30 can record the vehicle information provided by the vehicle 10 in the database. The data management server 30 may include a central processing unit (CPU), an application processor (AP), a graphics processing unit (GPU), a neural network processing unit (NPU), an image signal processor, etc., and can perform various data processing or calculations.

[0072] According to some embodiments, the data management server 30 can assist with updating the software of the autonomous driving platform installed in the vehicle 10, updating the battery management software, updating the navigation map, etc., and can store driving information, battery status information, black box video data, etc. provided by the vehicle 10 for a certain period of time. In addition, the data management server 30 can be configured to perform a variety of functions related to the processing, management, and storage of information and data related to the vehicle 10.

[0073] Figure 2 is a diagram illustrating the process by which driving control and energy management are performed in a vehicle according to some embodiments disclosed in this document.

[0074] Referring to Figure 2, the computing system 300 can process calculations related to the driving control of the vehicle 10 and / or calculations related to energy management functions. To this end, the computing system 300 can receive data corresponding to driving information and / or battery status information from the communication module 100, the sensor module 200, and / or the battery 400. According to some embodiments, the computing system 300 can be adapted to an autonomous driving platform.

[0075] According to some embodiments, driving control for the vehicle 10 may include controlling driving-related variables such as the vehicle 10's position, speed, acceleration, direction of travel, engine / motor rotation speed, gear ratio, suspension damping, and regenerative braking level, based on driving information relating to the vehicle 10's movement. For example, the driving information may include object information relating to objects around the vehicle 10, and behavior information relating to the vehicle 10's behavior. The object information may include the type and number of surrounding objects, their distance from the vehicle 10, their relative position to the vehicle 10, their ground position, relative speed, ground speed, relative acceleration, and ground acceleration. The behavior information may include the vehicle 10's position, travel path, distance traveled, speed, acceleration, steering angle, yaw, pitch, and roll. According to some embodiments, driving control may include controlling acceleration, deceleration, steering, and combinations thereof for the autonomous driving of the vehicle 10.

[0076] According to some embodiments, the energy management functions performed on the vehicle 10 may include generating and / or providing status diagnosis, life prediction, operation control (e.g., cell balancing), charging guidance, etc., of the battery 400 based on driving information of the vehicle 10 and / or battery status information provided from the battery 400. For example, the battery status information may include voltage information, current information, temperature information, state of charge (SOC) information, state of health (SOH) information, and combinations thereof, and may further include cumulative charging current, cumulative discharging current, cumulative charging energy, cumulative discharging energy, insulation resistance, relay status, etc.

[0077] According to some embodiments, the computing system 300 can execute driving control software that determines and implements driving control for the vehicle 10. For example, the driving control software can determine driving control, including acceleration, deceleration, steering, and combinations thereof, for autonomous driving of the vehicle 10 by controlling the drive system 500 based on driving information provided by the communication module 100 and / or the sensor module 200. The driving control software can instruct the drive system 500 to execute the determined driving control. The driving control software can also further consider battery state information provided by the battery 400 to determine driving control to be executed by the drive system 500, including acceleration, deceleration, steering, and combinations thereof, for autonomous driving of the vehicle 10.

[0078] According to some embodiments, the computing system 300 can run energy management software in addition to driving control software. For example, the computing system 300 can run the driving control software and the energy management software alternately or simultaneously. According to some embodiments, the computing system 300 can run energy management software based on battery status information provided by the battery management module 420 of the battery 400. In some embodiments, the management module 420 is or can be a battery management system for the battery 400. In this regard, the management module 420 may include one or more hardware components such as processors and / or memory, software such as program instructions for running management software such as energy management software, or a combination thereof. The management functions of the energy management software may include functions that generate and / or provide status diagnostics, life prediction, operation control (e.g., cell balancing), charging guides, etc., for the battery 400. According to some embodiments, the management module 420 can measure voltage, current, temperature, etc., from the battery pack 410 and estimate the state of charge (SOC), state of health (SOH), etc. The battery pack 410 may include multiple battery modules, each battery module may include multiple battery cells.

[0079] In a typical electric vehicle, the vehicle's controller handles only calculations related to driving control, while calculations related to energy management functions are handled by the battery management module. In contrast, the computing system 300 can be configured to handle both calculations related to driving control and calculations related to energy management functions. With this configuration, the computing system 300 has a relatively much higher processing power than the battery management module 420, and can perform energy management functions. Therefore, the computing system can perform energy management of the vehicle 10 more stably and smoothly.

[0080] Furthermore, some of the calculations related to the energy management function of the vehicle 10 can be processed by the computing system 300, and the remaining calculations can be processed by the management module 420 of the battery 400. By distributing the calculations related to the energy management function to the computing system 300 and the battery 400 in this way, the energy management of the vehicle 10 can be performed more stably and smoothly. In addition, it becomes possible to lower the processing requirements of the management module 420 provided in the battery 400, the energy requirements of the management module 420, or the specifications of both.

[0081] Figure 3 is a diagram illustrating a first computing system according to some embodiments disclosed in this document.

[0082] Referring to Figure 3, the diagram illustrates how, within the vehicle 10, the first computing system 301 manages first calculations related to driving control and second calculations related to energy management based on driving information provided by the sensor module 200. According to some embodiments, the first computing system 301 can be adapted to an autonomous driving platform.

[0083] According to some embodiments, the first computing system 301 may include an interface circuit 310 and at least one processor 320 operationally coupled to the interface circuit 310. However, it is not limited thereto, and some elements may be omitted from the first computing system 301, and other general-purpose elements may be further included in the first computing system 301.

[0084] In the following, any function and / or operation performed by at least one processor 320 can be interpreted as being performed by the first computing system 301 in the vehicle 10.

[0085] At least one processor 320 of the first computing system 301 can be configured to analyze a first calculation relating to the driving control of the vehicle 10 and a second calculation relating to the energy management of the vehicle 10. According to some embodiments, at least one processor 320 of the first computing system 301 can process the first calculation relating to the driving control of the vehicle 10 by executing the driving control software 350, and can process the second calculation relating to the energy management of the vehicle 10 by executing the energy management software 360. As described above, the first and second calculations can be processed alternately or simultaneously, and for this purpose, analysis of the first and second calculations can be performed. According to some embodiments, the analysis of the first and second calculations can include a comparison of the amount of computation, a comparison of computation time, an analysis of urgency, and so on.

[0086] At least one processor 320 of the first computing system 301 can be configured to acquire driving information relating to the movement of the vehicle 10. According to some embodiments, driving information relating to the movement of the vehicle 10 can be acquired by a sensor module 200. According to some embodiments, the driving information can include object information and behavior information. Object information may include the type and number of surrounding objects, the distance to the vehicle 10, their position relative to the vehicle 10, their position on the ground, their relative speed, their ground speed, their relative acceleration, their ground acceleration, etc., and behavior information may include the position of the vehicle 10, its travel path, its distance traveled, its speed, its acceleration, its steering angle, its yaw, pitch, its roll, etc.

[0087] At least one processor 320 of the first computing system 301 can be configured to manage the processing of the first and second operations based on driving information. According to some embodiments, when the processing of the first and second operations is managed, either the first or second operation may be processed before the other, or the first and second operations may be processed in parallel and simultaneously. For a scheme in which the first and second operations are processed alternately or sequentially, the processing priority of the first and second operations may be related to the order in which the first and second operations are executed. A scheme in which the first and second operations are processed in parallel and simultaneously means that the processing of the second operation begins before the processing of the first operation is completed, and for this reason, the processing priority between the first and second operations may include the ratio of computing resources allocated to the first and second operations, respectively. Furthermore, it should be recognized that computing resources can be allocated both sequentially and proportionally, such as by allocating a specific ratio of resources at the start time and adjusting the ratio over time, or by starting either the first or second operation before the other and then allocating computing resources to the two operations sequentially.

[0088] According to some embodiments, at least one processor 320 of the first computing system 301 can be configured to determine the processing priority of first and second operations based on driving information and to process the first and second operations according to the processing priority. When the vehicle 10 performs both driving control and energy management, driving information can be given priority in determining the processing order and amount of both operations, and battery status information can be additionally considered as needed.

[0089] According to some embodiments, during autonomous driving of the vehicle 10, the first calculation related to driving control may have a higher processing priority or processing priority than the second calculation related to energy management. For example, in the autonomous driving state of the vehicle 10, the first calculation may be completed at processing cycles of 0.1 seconds, 0.2 seconds, 0.3 seconds, 0.5 seconds, 1.0 seconds, etc., before the second calculation is processed, or the first and second calculations may be processed simultaneously at ratios such as 99:1, 98:2, 95:5, 90:10, 85:15, etc., depending on the processing priority.

[0090] Figure 4 is a diagram illustrating the process by which processing priorities are determined in a first computing system according to some embodiments disclosed in this document.

[0091] Referring to Figure 4, exemplary driving environments 420 and 440 of vehicle 10 are illustrated. Driving environment 420 includes surrounding objects 421, 422, 423, and 424 of vehicle 10, and driving environment 440 may include surrounding objects 441, 442, 443, and 444 of vehicle 10.

[0092] In driving environment 420, surrounding objects 421, 422, 423, and 424 can refer to road shoulders, pedestrian walkways, roadways, oncoming roadways, etc., and in driving environment 440, surrounding objects 441, 442, 443, and 444 can refer to pedestrians, parked vehicles, moving vehicles, oncoming vehicles, etc. Surrounding objects in driving environment 420 and driving environment 440 can be detected by sensor data generation by the sensor module 200 and sensor data processing by the computing system 300, and object information can be formed from this information.

[0093] According to some embodiments, the driving information may include behavioral information relating to the behavior of the vehicle 10 and object information relating to objects surrounding the vehicle 10, and at least one processor 320 of the first computing system 301 may determine the processing priority such that the first operation takes precedence over the second operation if at least one of the behavioral information overload and object information overload occurs. As one example, the behavioral information overload may be based on the amount of driving information input data that exceeds a critical value within a given amount of time. This may be exceeding a critical number of data points or a critical amount of space required to store the input data within a few seconds or a few processing cycles of the first computing system 301. As another example, the behavioral information overload may be based on the output from the computing system. This may be a measure of latency that exceeds a critical value, and may be a critical amount of time or a critical percentage of the operation being delayed. At least one processor 320 of the first computing system 301 may determine that the first and second operations have equivalent processing priority if neither the behavioral information overload nor the object information overload occurs.

[0094] For example, an overload of behavioral information includes situations where the frequency and magnitude of fluctuations in the vehicle 10's speed changes, deceleration, and / or steering, which may be due to acceleration, are high, resulting in an excessive amount of behavioral information. An overload of object information includes situations where the number, types, and movements of surrounding objects 421, 422, 423, 424 or surrounding objects 441, 442, 443, 444 are numerous and complex. In such behavioral information or object information overload situations, it is preferable to prioritize processing the first operation over the second operation to ensure stable driving control.

[0095] According to some embodiments, the vehicle 10 should determine its driving strategy in real time based on the number, shape, position, and speed of objects recognized during driving control, and the amount of computation for the first operation related to driving control may vary depending on the amount of driving information. Therefore, when the number of surrounding objects is less than a certain number, or when it is determined that the position and speed of surrounding objects do not affect the driving of the vehicle 10, energy management can be given priority over driving control.

[0096] According to some embodiments, longitudinal control, which corresponds to acceleration and deceleration during the driving control of the vehicle 10, and lateral control, which corresponds to heading and steering, can be distinguished, and in the case of lateral control, which is expected to require a larger amount of computation, the first calculation can be processed preferentially, while in the case of longitudinal control, the priority of the first calculation can be relatively lower.

[0097] According to some embodiments, both longitudinal and lateral control are required, and / or the computational load of the driving control software 350 becomes very large, such as when there are many types and numbers of surrounding objects and complex movements, and the driving control software 350 is busy, then the first computing system 301 can process the first calculation as the main calculation, or process only the first calculation, with a higher priority level than when the driving control software 350 is not busy. If the first calculation is processed as the main calculation or exclusively, at least a portion of the second calculation may not be processed by the first computing system 301. In this case, the second calculation may be processed by the management module 420 or the data management server 30, and the results may be transmitted to the first computing system 301. In other words, calculations stated in this disclosure to be performed by the management module 420 may, additionally or alternatively, be performed outside the management module, such as the management module 420 or other processing components or servers communicatively connected to the vehicle 10.

[0098] According to some embodiments, at least one processor 320 of the first computing system 301 can be configured to determine processing priority based on the periodic amount of driving information received and the periodic amount of processing of the first operation. The period for determining processing priority depends on the amount of input data typically received, the type of operation being performed, the amount of processing components available for the operation, and other factors, and may vary between different computing systems. For example, if the amount of driving information received per unit time (reception rate) from the sensor module 200 exceeds a critical reception rate, the processing priority can be determined so that the first operation takes precedence over the second operation, as the time required for processing this in the first computing system 301 is expected to increase. On the other hand, the amount of processing per unit time (processing rate) of the first operation may vary depending on the complexity of the driving information, and if the amount of processing per unit time of the first operation exceeds a critical processing rate, the processing priority can be determined so that the first operation takes precedence over the second operation.

[0099] According to some embodiments, at least one processor 320 of the first computing system 301 can be configured to determine whether or not an energy management priority event occurs based on battery state information relating to the battery 400 of the vehicle 10, and if it is determined that a priority event has occurred, to process an operation corresponding to the priority event, and then process a first operation and a second operation according to the processing priority.

[0100] For example, if an abnormality is detected in the battery status information, or if it is determined that energy management should take precedence over driving control in order to maintain and manage battery 400, it can be determined that an energy management priority event has occurred. When a priority event occurs, the corresponding calculation is processed preferentially, and then the first and second calculations can be processed according to the processing priority.

[0101] According to some embodiments, when the vehicle 10 starts driving, energy management such as battery condition diagnosis or remaining charge detection can be prioritized in the process of inputting a destination and setting a route, reflecting the charge state (SOC) and / or health state (SOH) of the battery 400, in order to eliminate routes that cannot be completed. According to some embodiments, when the vehicle 10 starts driving, or when a charging station is set as the destination, energy management can be prioritized to provide a charging guide for the battery 400. In this case, the charging guide can be determined based on past charging patterns and the degree of battery degradation. According to some embodiments, when an update of the driving control software 350 is in progress or scheduled, energy management can be prioritized to ensure sufficient battery charge for the completion of the update.

[0102] Figure 5 is a diagram illustrating the process by which processing priority is calculated in a first computing system according to some embodiments disclosed in this document.

[0103] Referring to Figure 5, a graph 500 is shown illustrating the process by which processing priority is calculated in the first computing system 301. Graph 500 shows the distribution structure of computing resources (R) over time (t).

[0104] According to some embodiments, at least one processor 320 of the first computing system 301 can be configured to process the first and second operations simultaneously by calculating the computation priority of the first operation relative to the second operation based on running information and distributing computation resources based on the computation priority. Computation resources may include, but are not limited to, one or a combination of processing resources or memory resources included in the computing system used to perform the first and second operations described herein. For example, processing resources may include the number of CPUs or cores allocated for a particular operation, the number of instruction words or instruction threads executed to perform a particular operation, the amount of memory space or the number of memory devices reserved for a particular operation, or the speed of the processing cycle in which a particular operation is performed.

[0105] In Graph 500, the computing resources (R0) may represent the sum of the computing resources possessed by the first computing system 301. The computing resources (R0) can be allocated to a first resource (R1) for processing first calculations related to driving control, and a second resource (R2) for processing second calculations related to energy management. According to some embodiments, the allocation of computing resources (R0) can change each time an event occurs related to the driving of the vehicle 10 or the battery (E1, ..., E5).

[0106] According to some embodiments, at least one processor 320 of the first computing system 301 can be configured to determine whether or not an energy management priority event occurs based on battery status information relating to the battery 400 of the vehicle 10, and if it is determined that a priority event has occurred, to set a priority upper limit based on the characteristics of the priority event, and to recalculate the calculation priority taking the priority upper limit into consideration.

[0107] In some embodiments, in Graph 500, event (E5) is a priority event for energy management, and for example, a priority event may include situations where an abnormal state occurs in the battery status information, situations where the battery level and fuel are low, situations where the destination is set to a charging station, and situations where an update of the driving control software is scheduled. The priority upper limit can be set to R3 / R0. This ensures that even if an event (E6) occurs after event (E5) that should decrease the weight of the second calculation (R4 / R0) and increase the weight of the first calculation (R3 / R0), the ratio of the first and second calculations (R3:R4) does not change due to the limitation of the priority upper limit.

[0108] According to some embodiments, at least one processor 320 of the first computing system 301 may be configured to transmit at least a portion of the second operation to the management module 420 of the battery 400 when the operation priority is set to less than a priority threshold, and to process the entire second operation based on the operation results for at least a portion of the second operation provided by the management module 420.

[0109] Priority threshold values ​​can be pre-set to numerical values ​​such as 0.5%, 1.0%, 2.0%, and 5.0%. If the computation priority of the first operation relative to the second operation falls below the priority threshold value due to an overload of behavioral information or object information as described above, it may be difficult to process the second operation without delay using only the computational resources (R2 / R0) allocated to energy management. In this case, the computational resources of the battery 400's management module 420 can be utilized to replenish the insufficient computational resources. At least a portion of the results of the second operation processed by the management module 420 can be transmitted to the first computing system 301, and the second operation can be completed based on this.

[0110] Figure 6 is a diagram illustrating the steps that constitute the operation method of the first computing system according to some embodiments disclosed in this document.

[0111] Referring to Figure 6, the operation method 600 of the first computing system 301 may include steps 610 to 630. However, it is not limited thereto, and some steps may be omitted or general steps may be added, and the steps of the operation method 600 may be executed in an order different from that shown.

[0112] Steps 610 to 630 of the operation method 600 can be performed by at least one processor 320 which is operationally coupled to the interface circuit 310. The operation method 600 of the first computing system 301 can consist of steps that are processed chronologically in the first computing system 301. Therefore, even if the details are omitted below, the details described above for the first computing system 301 can also be applied to the operation method 600.

[0113] In step 610, the first computing system 301 can analyze a first calculation related to vehicle driving control and a second calculation related to vehicle energy management. In step 620, the first computing system 301 can acquire driving information related to vehicle driving. In step 630, the first computing system 301 can manage the processing of the first and second calculations based on the driving information.

[0114] According to some embodiments, the operation method 600 of the first computing system 301 can be implemented in the form of a computer program stored on a computer-readable storage medium. That is, the computer program includes instructions for implementing the operation method 600 of the first computing system 301, and the instructions of the program can be stored on a computer-readable storage medium. The computer program may include a mobile application.

[0115] For example, computer-readable storage media can include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute computer program instructions, such as ROM, RAM, and flash memory. Computer program instructions can include machine code generated by a compiler and high-level language code that can be executed by a computer using an interpreter or the like.

[0116] Figure 7 is a diagram illustrating a second computing system according to some embodiments disclosed in this document.

[0117] Referring to Figure 7, a second computing system 302 manages a first calculation related to driving control and a second calculation related to energy management within the vehicle 10, based on battery state information provided by the battery 400. According to some embodiments, the second computing system 302 can be adapted to an autonomous driving platform.

[0118] According to some embodiments, the second computing system 302 may include an interface circuit 310 and at least one processor 320 operationally coupled to the interface circuit 310. However, it is not limited thereto, and some elements may be omitted in the second computing system 302, and other general-purpose elements may be further included in the second computing system 302.

[0119] In the following, any function and / or operation performed by at least one processor 320 can be interpreted as being performed by the second computing system 302 in the vehicle 10.

[0120] At least one processor 320 of the second computing system 302 can be configured to analyze a first calculation relating to the driving control of the vehicle 10 and a second calculation relating to the energy management of the vehicle 10. According to some embodiments, at least one processor 320 of the second computing system 302 can process the first calculation relating to the driving control of the vehicle 10 by executing the driving control software 350, and can process the second calculation relating to the energy management of the vehicle 10 by executing the energy management software 360. As described above, the first and second calculations can be processed alternately or simultaneously, and for this purpose, analysis of the first and second calculations can be performed. According to some embodiments, the analysis of the first and second calculations can include a comparison of the amount of computation, a comparison of computation time, an analysis of urgency, and so on.

[0121] At least one processor 320 of the second computing system 302 may be configured to acquire battery state information relating to the battery 400 of the vehicle 10. According to some embodiments, the battery state information may include voltage information, current information, temperature information, state of charge (SOC) information, state of health (SOH) information, cumulative charging current, cumulative discharging current, cumulative charging energy, cumulative discharging energy, insulation resistance, relay status, and combinations thereof.

[0122] At least one processor 320 of the second computing system 302 can be configured to manage the processing of the first and second operations based on battery status information. According to some embodiments, when the processing of the first and second operations is managed, either the first or second operation may be processed before the other, or the first and second operations may be processed in parallel and simultaneously. For a configuration in which the first and second operations are processed alternately, a processing priority can be determined for the first and second operations, and for a configuration in which the first and second operations are processed in parallel and simultaneously, a processing priority can be determined between the first and second operations.

[0123] According to some embodiments, at least one processor 320 of the second computing system 302 can be configured to determine the processing priority of the first and second operations based on battery status information and to process the first and second operations according to the processing priority. When the vehicle 10 performs both driving control and energy management, battery status information can be referenced preferentially to determine the processing order and amount of both operations, and driving information can be additionally considered as needed.

[0124] According to some embodiments, when the vehicle 10 is not autonomously driving, for example, when the vehicle 10 is stopped, the second calculation related to energy management may have the same or a higher processing priority than the first calculation related to driving control. For example, when the vehicle 10 is stopped waiting for a traffic light, the second calculation may be completed at processing cycles of 0.1 seconds, 0.2 seconds, 0.3 seconds, 0.5 seconds, 1.0 seconds, etc., before the first calculation is processed, or the first and second calculations may be processed simultaneously at ratios of 90:10, 85:15, 80:20, 75:25, 70:30, 65:35, etc., depending on the processing priority.

[0125] Figure 8 is a diagram illustrating how battery status information is utilized in a second computing system according to some embodiments disclosed in this document.

[0126] Referring to Figure 8, the process of generating battery status information 810 by the management module 420 in the vehicle 10 and using this information to perform priority adjustment 830 or priority adjustment 850 for the first and second calculations is illustrated.

[0127] According to some embodiments, the management module 420 can measure voltage, current, temperature, etc., from the battery pack 410 and estimate the state of charge (SOC), state of health (SOH), etc., to generate battery state information 810. According to some embodiments, the estimation of the state of charge (SOC) or state of health (SOH) can be performed by a second computing system 302 instead of the management module 420.

[0128] The second computing system 302 can perform priority adjustments 830 regarding which of the first calculations related to driving control and the second calculations related to energy management should be given more priority, or priority adjustments 850 regarding the ratio in which the first and second calculations should be performed simultaneously, based on the battery status information 810.

[0129] According to some embodiments, the battery state information 820 may include battery temperature information, and at least one processor 320 of the second computing system 302 may determine the processing priority based on the battery temperature information such that the first operation takes precedence over the second operation if the battery is not overheating, and determine that the first and second operations have equal processing priority if the battery is overheating.

[0130] Whether or not battery overheating occurs can be determined by whether the average temperature of battery 400, based on battery temperature information, exceeds a preset critical temperature during specific time intervals such as 10 seconds, 15 seconds, 30 seconds, 1 minute, and 3 minutes. Instead of the average value, other representative values ​​such as the median can be used.

[0131] If battery overheating occurs, the second computing system 302 may need to process the second calculation for energy management instead of the management module 420, and therefore the priority of the second calculation can be set relatively higher. Conversely, if battery overheating does not occur, the first calculation can be processed in priority over the second calculation. According to some embodiments, having the same priority as the second calculation may mean that the second computing system 302 processes the calculations in the order in which they occur without distinguishing between the first and second calculations. According to some embodiments, if battery overheating occurs, the processing priority can be determined so that the second calculation takes precedence over the first calculation.

[0132] According to some embodiments, warnings regarding thermal runaway of the battery 400 can be issued in stages based on battery temperature information. Thermal runaway can occur due to mechanical, electrical, or thermal abnormal conditions or internal short circuits in the battery 400, and may lead to a fire in the vehicle 10. When signs of thermal runaway are detected by battery status information 810, including battery temperature information, the second computing system 302 can reduce or interrupt the use of the battery 400. To this end, the driving control software 350 can restrict at least some of the driving functions of the vehicle 10. For example, depending on the stage of thermal runaway risk, restrictions can be imposed on driving assistance functions, vehicle speed, air conditioning, display, and sport driving modes.

[0133] According to some embodiments, if the temperature of the battery 400 exceeds a critical temperature such as 40°C, 45°C, 50°C, 55°C, or 60°C, the energy management software 360 ​​or management module 420 of the second computing system 302 can perform derating control on the battery 400. According to some embodiments, when derating control is performed, the second computing system 302 can set a higher processing priority or processing priority for the second operation relative to the first operation.

[0134] According to some embodiments, at least one processor 320 of the second computing system 302 can be configured to determine processing priority based on the periodic amount of battery status information 810 received, for example, the amount received per hour, and the periodic amount of processing of the second operation, for example, the amount processed per hour. For example, if the amount of battery status information 810 received per hour (reception rate) provided by the management module 420 exceeds a critical reception amount, the processing priority can be determined so that the first operation does not take precedence over the second operation, as it is expected that the time required for the second computing system 302 to process this will increase. On the other hand, if the amount of processing (processing rate) of the second operation varies depending on the complexity of the battery status information 810, and the amount of processing of the second operation exceeds a critical processing amount, the processing priority can be determined so that the first operation does not take precedence over the second operation.

[0135] According to some embodiments, at least one processor 320 of the second computing system 302 can be configured to determine whether or not a priority event for driving control occurs based on driving information relating to the driving of the vehicle 10, and if it is determined that a priority event has occurred, to process an operation corresponding to the priority event, and then process a first operation and a second operation according to the processing priority.

[0136] For example, if an abnormality is detected in the driving information, if the amount of driving information received and processed increases excessively, and it is determined that driving control should take precedence over energy management, or if it is expected that vehicle 10 will pass through a place with a high difficulty of driving, it can be determined that a driving control priority event has occurred. When a priority event occurs, the corresponding calculation is processed preferentially, and then the first and second calculations can be processed according to the processing priority.

[0137] Figure 9 is a diagram illustrating the process by which processing priority is calculated in a second computing system according to some embodiments disclosed in this document.

[0138] Referring to Figure 9, a graph 900 is shown illustrating the process by which processing priority is calculated in the second computing system 302. Graph 900 shows the distribution structure of computing resources (R) over time (t).

[0139] According to some embodiments, at least one processor 320 of the second computing system 302 can be configured to process the first and second operations simultaneously by calculating the computation priority of the second operation relative to the first operation based on battery status information and distributing computation resources based on the computation priority.

[0140] In Graph 900, the computing resources (R0) may represent the sum of the computing resources possessed by the second computing system 302. The computing resources (R0) can be allocated to a first resource (R1) for processing first calculations related to driving control, and a second resource (R2) for processing second calculations related to energy management. According to some embodiments, the allocation of computing resources (R0) can change each time an event occurs related to the driving of the vehicle 10 or the battery (E1, ..., E5).

[0141] According to some embodiments, at least one processor 320 of the second computing system 302 can be configured to determine whether a priority event for driving control occurs based on driving information relating to the driving of the vehicle 10, and if it is determined that a priority event has occurred, to set a priority upper limit based on the characteristics of the priority event, and to recalculate the calculation priority taking the priority upper limit into consideration.

[0142] In some embodiments, in graph 900, event (E5) is a priority event for driving control. For example, priority events can include situations where the number and types of objects surrounding the vehicle 10 become large and complex, situations where the longitudinal control amount related to acceleration / deceleration and the lateral control amount related to heading / steering of the vehicle 10 increase significantly, and situations where a large amount of calculation is required due to driving information restricted by worsening weather conditions. The priority upper limit can be set to R4 / R0. This ensures that even if an event (E6) occurs after event (E5) that should increase the weight of the second calculation (R4 / R0) and decrease the weight of the first calculation (R3 / R0), the ratio of the first and second calculations (R3:R4) is not changed due to the limitation of the priority upper limit.

[0143] According to some embodiments, at least one processor 320 of the second computing system 302 may be configured to transmit at least a portion of the second operation to the management module 420 of the battery 400 when the operation priority is set to a priority threshold value or higher, and to process the entire second operation based on the operation results for at least a portion of the second operation provided by the management module 420.

[0144] Priority threshold values ​​can be pre-set to values ​​such as 1.0%, 2.0%, 5.0%, and 10.0%. In situations such as the aforementioned thermal runaway of the battery, if the calculation priority of the second calculation relative to the first calculation exceeds the priority threshold value, it may affect the smooth operation of the driving control software 350 of the second computing system 302. To prevent the driving control of the vehicle 10 from being affected in this way, the computing resources of the battery 400's management module 420 can be utilized. At least a portion of the results of the second calculation processed by the management module 420 can be transmitted to the second computing system 302, and the second calculation can be completed based on this.

[0145] Figure 10 is a diagram illustrating the steps that constitute the operation method of a second computing system according to some embodiments disclosed in this document.

[0146] Referring to Figure 10, the operation method 1000 of the second computing system 302 may include steps 1010 to 1030. However, it is not limited thereto, and some steps may be omitted or general steps may be added, and the steps of the operation method 1000 may be executed in an order different from that shown.

[0147] Steps 1010 to 1030 of the operation method 1000 can be performed by at least one processor 320 which is operationally coupled to the interface circuit 310. The operation method 1000 of the second computing system 302 can consist of steps that are processed chronologically in the second computing system 302. Therefore, even if the details are omitted below, the details described above for the second computing system 302 can also be applied to the operation method 1000.

[0148] In step 1010, the second computing system 302 can analyze a first calculation related to vehicle driving control and a second calculation related to vehicle energy management. In step 1020, the second computing system 302 can acquire battery status information related to the vehicle's battery. In step 1030, the second computing system 302 can manage the processing of the first and second calculations based on the battery status information.

[0149] According to some embodiments, the operation method 1000 of the second computing system 302 can be implemented in the form of a computer program stored on a computer-readable storage medium. That is, the computer program may include instructions for implementing the operation method 1000 of the second computing system 302, and the instructions of the program may be stored on a computer-readable storage medium. The computer program may include a mobile application.

[0150] For example, computer-readable storage media can include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute computer program instructions, such as ROM, RAM, and flash memory. Computer program instructions can include machine code generated by a compiler and high-level language code that can be executed by a computer using an interpreter or the like.

[0151] Figure 11 is a diagram illustrating a third computing system according to some embodiments disclosed in this document.

[0152] Referring to Figure 11, the third computing system 303 inside the vehicle 10 distributes battery-related calculations to a first calculation processed by the third computing system 303 and a second calculation processed by the battery 400, based on battery state information provided by the battery 400. According to some embodiments, the third computing system 303 can be adapted to an autonomous driving platform.

[0153] According to some embodiments, the third computing system 303 may include an interface circuit 310 and at least one processor 320 operationally coupled to the interface circuit 310. However, it is not limited thereto, and some elements may be omitted from the third computing system 303, and other general-purpose elements may be further included in the third computing system 303.

[0154] In the following, any function and / or operation performed by at least one processor 320 can be interpreted as being performed by the third computing system 303 in the vehicle 10.

[0155] At least one processor 320 of the third computing system 303 may be configured to acquire battery state information from the battery 40 of the vehicle 10 regarding the state of the battery 40. According to some embodiments, the battery state information may include voltage information, current information, temperature information, state of charge (SOC) information, state of health (SOH) information, cumulative charge current, cumulative discharge current, cumulative charge energy, cumulative discharge energy, insulation resistance, relay state, and combinations thereof.

[0156] At least one processor 320 of the third computing system 303 can be configured to process at least partially calculations related to the energy management of the vehicle 10 using battery status information. According to some embodiments, energy management may include management functions such as battery status measurement, battery level estimation, battery life prediction, and battery cell balancing, and at least a portion of the calculations corresponding to each management function may be performed by the third computing system 303.

[0157] At least one processor 320 of the third computing system 303 can be configured to process calculations and provide the resulting information obtained to the battery 400. If only at least a portion of the calculations related to energy management are processed by the third computing system 303 and the results are provided to the battery 400, the remaining portion to complete the calculations can be processed by the battery 400's management module 420.

[0158] According to some embodiments, the calculations related to energy management may include a first calculation that is at least partially processed by at least one processor 320, and a second calculation that is processed by the battery 400. According to some embodiments, the energy-related calculations are divided into a first calculation and a second calculation, the first calculation may be processed by a third computing system 303, and the second calculation may be processed by a management module 420 of the battery 400. This method allows the third computing system 303, which has high computing processing capabilities, to participate in the energy-related calculations, thereby enabling more stable energy management of the vehicle 10.

[0159] Figure 12 is a diagram illustrating a method for calculating the ratio of the first and second operations in a third computing system according to some embodiments disclosed in this document.

[0160] Referring to Figure 12, the third computing system 303 in the vehicle 10 adjusts the calculation ratio 1290 based on the characteristics 1250 of calculations related to energy management and the battery status information 1270 of the battery 400.

[0161] In the vehicle 10, energy management 1210 can be performed on the battery 400. According to some embodiments, energy management 1210 may include battery state measurement, battery charge estimation, battery life prediction, battery cell balancing, etc. Energy management 1210 can be achieved by energy-related calculations 1230, and energy-related calculations 1230 may have calculation characteristics 1250 depending on the amount and type of calculation. On the other hand, the battery 400 may have battery state information 1270 such as voltage, current, temperature, state of charge (SOC), state of health (SOH), cumulative charge amount, and cumulative discharge amount.

[0162] According to some embodiments, at least one processor 320 of the third computing system 303 may be configured to adjust the ratio of first and second operations based on the characteristics 1250 of operations related to energy management and battery status information 1270. Adjusting the operation ratio 1290 of first and second operations may mean adjusting the ratio at which energy-related operations 1230 are distributed to the management module 420 of the third computing system 303 and the battery 400.

[0163] The calculation ratio 1290 can be adjusted based on the calculation characteristics 1250 and the battery status information 1270. For example, if the amount and complexity of calculations are high, such as when the energy-related calculations 1230 have a multi-stage calculation procedure, the management module 420 can allocate more calculations to the third computing system 303. Similarly, if the battery status information 1270 has a complex pattern or high data variability, the management module 420 can also allocate more calculations to the third computing system 303.

[0164] According to some embodiments, the management module 420 can collect battery status information 1270 and transmit it to the third computing system 303, which can then process all energy-related calculations 1230 using the battery status information 1270 and return the calculation results to the management module 420. According to some embodiments, the energy-related calculations 1230 can be performed by the driving control software 350 and / or energy management software 360 ​​of the third computing system 303.

[0165] According to some embodiments, the battery state information 1270 may include SOC information during driving, indicating the range of charge states (SOC) in which the vehicle 10 was driven, and similarly may include temperature information during driving. The battery state information 1270 may further include charging current information, SOC / DOD information used in the most recent 16 cycles, and cumulative energy per mile. In this regard, complex patterns in battery state information may refer to patterns of charging current, SOC / DOD, cumulative energy, etc., that have profiles that do not closely match or compare with typical profiles of battery state information from similar batteries, for example, battery state information obtained from a training dataset, over several cycles.

[0166] According to some embodiments, at least one processor 320 of the third computing system 303 can be configured to increase the weight of the first calculation to the second calculation if the energy-related calculation 1230 has characteristics that involve the driving control of the vehicle 10. For example, when regenerative braking is performed on the vehicle 10, the remaining charge of the battery 400 may affect whether or not regenerative braking is possible, so the energy-related calculation 1230 can be involved in the driving control. In this case, when the energy-related calculation 1230 affects the driving control, the weight of the first calculation, which is processed with high computing power, can be increased for smooth driving control.

[0167] According to some embodiments, if the power that can be charged by regenerative braking is limited in the battery 400, the management module 420 informs the third computing system 303 of this, and accordingly, the driving control software 350 of the third computing system 303 can adjust the level of regenerative braking. When the level of regenerative braking is adjusted, the amount of charge and braking force can be changed.

[0168] According to some embodiments, the battery state information 1270 may include temperature information, and at least one processor 320 of the third computing system 303 may be configured to increase the weight of the first operation to the second operation if the battery temperature, according to the temperature information, is above a critical temperature. For example, if the battery temperature exceeds a critical temperature such as 40°C, 45°C, 50°C, 55°C, or 60°C, the weight of the second operation processed by the management module 420 may be reduced in order to restore the battery temperature to a normal range and prevent thermal runaway of the battery. In some examples, the weight of the second operation processed by the management module 420 may be repeatedly reduced until the battery temperature does not exceed a critical temperature, thereby avoiding the risk of thermal runaway of the battery.

[0169] According to some embodiments, the management module 420 can perform cooling and / or heating control to regulate the temperature of the battery pack 410 of the battery 400. In this case, the management module 420 informs the third computing system 303 of the status of the temperature control, and in response, the energy management software 360 ​​of the third computing system 303 can predict the change in the battery temperature due to the temperature control and reflect the prediction result in the subsequent processing of the first calculation.

[0170] According to some embodiments, at least one processor 320 of the third computing system 303 may be further configured to acquire driving information relating to the movement of the vehicle 10, and at least one processor 320 of the third computing system 303 may be configured to adjust the ratio by additionally considering the driving information. For example, if additional driving information such as the current speed of the vehicle 10 and the movement of surrounding objects is taken into consideration, situations may arise where it is difficult to allocate the computing resources of the third computing system 303 to energy-related calculations 1230. Therefore, if an increase in computing resources for driving control is expected, the computing load on the management module 420 may increase.

[0171] According to some embodiments, at least one processor 320 of the third computing system 303 can be configured to estimate the state of the battery 400 based on driving information, generate estimated state information, and process the first calculation using the estimated state information. For example, while the battery state information 1270 is information directly measured from the battery 400 by the management module 420, the estimated state information can be estimated by considering the vehicle 10's mileage, speed, and energy consumption. When utilizing the estimated state information, the third computing system 303 can process the first calculation without interruption even if the battery state information 1270 is temporarily unavailable.

[0172] According to some embodiments, the energy management software 360 ​​of the third computing system 303 can generate estimated state information based on driving information and correct for errors by comparing it with battery state information 1270 measured directly from the battery 400. The error-corrected estimated state information can be used for subsequent energy-related calculations 1230 or for controlling the battery pack 410.

[0173] According to some embodiments, at least one processor 320 of the third computing system 303 may be configured to generate estimated state information based on driving information using a state estimation model, compare the estimated state information with battery state information 1270 actually measured by the battery 400, and update the state estimation model. For example, the state estimation model may be updated in a way that reduces the error between the estimated state information and the battery state information 1270. According to some embodiments, the state estimation model may be an AI model that is learned and updated using a variety of machine learning techniques based on neural network structures. As the model parameters are optimized through continuous updates, the state estimation model can generate estimated state information that is substantially identical to the battery state information 1270 actually measured by the battery 400.

[0174] According to some embodiments, the energy management software 360 ​​of the third computing system 303 and the management module 420 of the battery 400 can process energy-related calculations 1230 in stages. For example, the energy management software 360 ​​can calculate the state of charge (SOC) and / or state of health (SOH) based on voltage, current, temperature data, etc., of the battery 400. The management module 420 can perform control operations such as cell balancing based on the SOC and / or SOH, and can further provide the result data of the control operations to the energy management software 360. The energy management software 360 ​​can recalculate the SOC and / or SOH or perform other management functions based on the result data.

[0175] Figure 13 is a diagram illustrating the steps that constitute the operation method of a third computing system according to some embodiments disclosed in this document.

[0176] Referring to Figure 13, the operation method 1300 of the third computing system 303 may include steps 1310 to 1330. However, it is not limited thereto, and some steps may be omitted or general steps may be added, and the steps of the operation method 1300 may be executed in an order different from that shown.

[0177] Steps 1310 to 1330 of the operation method 1300 can be performed by at least one processor 320 which is operationally coupled to the interface circuit 310. The operation method 1300 of the third computing system 303 can consist of steps that are processed chronologically in the third computing system 303. Therefore, even if the details are omitted below, the details described above for the third computing system 303 can also be applied to the operation method 1300.

[0178] In step 1310, the third computing system 303 can obtain battery status information from the vehicle's battery regarding the state of the battery. In step 1320, the third computing system 303 can use the battery status information to at least partially process calculations related to the vehicle's energy management. In step 1330, the third computing system 303 can provide the battery with the result information obtained from processing the calculations.

[0179] According to some embodiments, the operation method 1300 of the third computing system 303 can be implemented in the form of a computer program stored on a computer-readable storage medium. That is, the computer program includes instructions for implementing the operation method 1300 of the third computing system 303, and the instructions of the program can be stored on a computer-readable storage medium. The computer program may include a mobile application.

[0180] For example, computer-readable storage media can include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute computer program instructions, such as ROM, RAM, and flash memory. Computer program instructions can include machine code generated by a compiler and high-level language code that can be executed by a computer using an interpreter or the like.

[0181] The terms "contains," "constitutes," and "possesses," as used above, mean, unless otherwise specified, that the component in question may be inherent, and should be interpreted as potentially including other components rather than excluding them. All terms, including technical and scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiments disclosed herein belong, unless otherwise defined. Commonly used terms, such as those defined in dictionaries, should be interpreted in accordance with their meaning in the context of the relevant technology and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this document.

[0182] The above description is merely illustrative of the technical concept disclosed herein, and a person with ordinary skill in the art to which the embodiments disclosed herein belong will be able to make various modifications and variations without departing from the essential characteristics of the embodiments disclosed herein. Therefore, the embodiments disclosed herein are for illustrative purposes only, not to limit the technical concept of the embodiments disclosed herein, and the scope of the technical concept disclosed herein is not limited by such embodiments. The scope of protection of the technical concept disclosed herein should be interpreted in accordance with the attached claims, and all technical concepts within an equivalent scope should be interpreted as being included in the scope of rights of this document.

[0183] In some embodiments of this disclosure, at least one processor of a vehicle's in-vehicle computing system may be implemented as a system-on-a-chip. In this context, the chip may provide all or part of the onboard computing functions of an autonomous driving platform. For example, calculations related to driving control and energy management may be performed using a single chip included in the vehicle. In such an example, the computing resources distributed between the driving control and energy management functions may refer to the computing resources available on the chip. Also in such an example, the interface circuit may be a single pin on the chip or another type of interface port. [Explanation of Symbols]

[0184] 1. Vehicle Management System 10 vehicles 20 Networks 30 Data Management Server 100 communication modules 200 Sensor Modules 300 Computing Systems 400 batteries 500 drive system 310 Interface Circuit 320 at least one processor 410 Battery Pack 420 Management Modules 350 Driving control software 360 Energy Management Software

Claims

1. It includes at least one processor that is operationally coupled to the vehicle's battery, The at least one processor has computing resources configured to perform at least a first operation relating to the driving control of the vehicle and a second operation relating to the energy management of the vehicle, The at least one processor obtains battery state information relating to the vehicle's battery from the battery, An autonomous driving platform configured to manage the allocation of computing resources for performing the first operation and computing resources for performing the second operation, at least in part, based on the battery state information.

2. The autonomous driving platform according to claim 1, wherein the allocation of the computing resources is based on the processing priority between the first and second operations, and the processing priority between the first and second operations is based on the battery status information.

3. The aforementioned battery status information includes battery temperature information, The at least one processor is In response to the indication that the battery is not overheating based on the battery temperature information, the processing priority is determined such that the first calculation has priority over the second calculation. The autonomous driving platform according to claim 2, configured to determine the processing priority such that the first calculation and the second calculation have equal priority to each other in response to an indication that the battery is overheating based on the battery temperature information.

4. The autonomous driving platform according to claim 2, wherein the processing priority is based on the amount of battery state information received during a predetermined time interval and the amount of processing of the second calculation during the predetermined time interval.

5. The autonomous driving platform according to claim 4, wherein the at least one processor is configured to set the processing priority so that the first operation takes precedence over the second operation in response to the amount of battery state information received that exceeds a critical amount.

6. The autonomous driving platform according to claim 4, wherein the at least one processor is configured to set the processing priority so that the first operation takes precedence over the second operation in response to the amount of battery state information received that does not exceed a critical amount.

7. The at least one processor is Obtain driving information regarding the vehicle's movement, Based on the aforementioned driving information, the occurrence of a driving priority event related to driving control is determined. The autonomous driving platform according to claim 2, configured to determine the processing priority of the first and second operations based on the driving priority event in response to the driving priority event.

8. The autonomous driving platform according to claim 7, wherein the driving priority event is one of the following weather-related events that require increased steering control, increased acceleration / deceleration control, or increased computation.

9. The allocation of the computing resources includes determining the ratio of the computing priority of the second operation to the first operation based on the battery status information, The autonomous driving platform according to claim 7, wherein the ratio of the computational priority is such that individual portions of the computational resources are assigned to the first computation and the second computation, respectively.

10. The at least one processor is Obtain battery status information regarding the battery of the vehicle, Based on the aforementioned driving information, the occurrence of a driving priority event related to driving control is determined. The autonomous driving platform according to claim 9, wherein, in response to the driving priority event, the ratio value of the calculation priority is set to a higher priority ratio value that gives priority to the second calculation over the first calculation by a predetermined maximum amount.

11. The at least one processor is In response to the ratio value of the calculation priority being equal to or greater than the priority ratio reference value, at least a portion of the second calculation is assigned to the battery management system of the battery. The autonomous driving platform according to claim 9, configured to process the second calculation based on a partial second calculation result received from the battery management system.

12. The autonomous driving platform further includes the battery, The battery includes the battery management system, The autonomous driving platform according to claim 11, wherein the battery management system is configured to perform at least a portion of the second calculation and to transmit the partial result of the second calculation to the at least one processor.

13. The autonomous driving platform according to claim 11, wherein the battery management system is operated remotely in part such that at least a portion of the partial second calculation result is received from a remote portion of the battery management system.

14. The autonomous driving platform according to claim 9, wherein the first and second operations are performed in parallel.

15. The allocation of the computational resources includes determining the order of the first and second operations based on the battery status information. The autonomous driving platform according to claim 1, wherein the order determines whether the computing resource performs the first or second operation first.

16. The autonomous driving platform according to claim 1, wherein the at least one processor and the computing resources are included in a system-on-chip.

17. The autonomous driving platform according to claim 16, wherein the system-on-chip comprises only one processing chip.

18. The autonomous driving platform according to claim 1, further comprising an interface circuit configured to operatively connect the at least one processor to one or more of the vehicle's sensors.

19. The autonomous driving platform according to claim 1, wherein at least one processor is included in the vehicle.

20. The autonomous driving platform according to claim 19, wherein the computing resources are included in the vehicle.

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