A computing system that provides energy management services in conjunction with autonomous driving, a method for operating the computing system, and a vehicle.

Abstract

A computing system according to one embodiment disclosed herein includes an autonomous driving control unit that controls the autonomous driving of a vehicle, and an energy management unit that provides services relating to the energy management of the vehicle, wherein the autonomous driving control unit sets the output of a drive system included in the vehicle, and the energy management unit determines a change in the internal resistance of a battery based on the driving data of the vehicle and battery data of a battery included in the vehicle, and sets the output current of the battery for the set output of the drive system based on the determined change in internal resistance.

Description

Technical Field

[0001] The present invention claims the benefit of priority based on Korean Patent Application No. 10-2023-0061372 filed on May 11, 2023 and Korean Patent Application No. 10-2023-0117973 filed on September 5, 2023, and all the contents disclosed in the documents of the Korean patent applications are incorporated herein by reference in their entirety.

[0002] Embodiments disclosed in this document relate to a computing system that provides an energy management service in cooperation with autonomous driving, a method of operating the computing system, and a vehicle.

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. With the advancement of artificial intelligence technology and various sensor technologies, research and development for improving the performance of hardware and software related to autonomous driving systems are also actively underway. Along with this, in recent years, autonomous driving systems for assisting vehicle autonomous driving have been developed or provided in the form of a single autonomous driving platform including various sensors and control units, and some electric vehicle manufacturers are mass-producing or developing autonomous driving electric vehicles based on the autonomous driving platform.

[0004] In order to further enhance the autonomous driving technology of electric vehicles, energy management of the vehicle is important. In this regard, during the process of a vehicle driving autonomously, various behaviors and events that determine driving scenarios can occur. Such events are inevitably closely related to energy consumption or energy management. However, general electric vehicles do not have an energy management function or do not consider the aspect of energy management at all.

[0005] Autonomous driving platforms that perform autonomous driving control generally do not communicate with systems that control battery energy management. Thus, the battery output current was set without considering energy losses due to changes in the driving environment or conditions during the autonomous driving process. For example, because energy losses due to the driving environment or conditions could not be precisely understood, the battery output current was conservatively set very high, or adjusted retrospectively after changes in the driving environment or conditions. This resulted in inefficient energy consumption and the generation of more emissions and / or greenhouse gases in the energy production process. Such emissions and / or greenhouse gases could have negative environmental impacts, such as causing climate change. [Overview of the project] [Problems that the invention aims to solve]

[0006] One objective of the embodiments disclosed herein is to provide a computing system, a method of operating the computing system, and a vehicle that can provide energy management services based on battery data, as well as autonomous driving control. The battery management function enables more economical driving on the autonomous driving platform compared to conventional autonomous vehicles, and as a result, the overall energy efficiency of the vehicle can be further improved and energy consumption reduced. Furthermore, the battery management function can be implemented on autonomous driving platforms of various types of vehicles, and energy efficiency can be broadly improved.

[0007] One objective of the embodiments disclosed in this document is to provide a computing system, a method of operating the computing system, and a vehicle that can set the output current of a battery in consideration of changes in the internal resistance of the battery due to the vehicle's driving environment and / or driving conditions.

[0008] 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]

[0009] A computing system according to one embodiment disclosed herein includes an autonomous driving control unit that controls the autonomous driving of a vehicle, and an energy management unit that provides services relating to the energy management of the vehicle, wherein the autonomous driving control unit sets the output of a drive system included in the vehicle, and the energy management unit determines a change in the internal resistance of a battery based on the driving data of the vehicle and battery data of a battery included in the vehicle, and sets the output current of the battery for the set output of the drive system based on the determined change in internal resistance.

[0010] In a computing system according to one embodiment disclosed herein, the energy management unit can determine the degree of energy loss due to the determined change in internal resistance and set the output current based on the determined degree of energy loss.

[0011] In a computing system according to one embodiment disclosed herein, the energy management unit can set the output current to a higher value when the determined degree of energy loss increases.

[0012] In a computing system according to one embodiment disclosed in this document, the energy management unit can use a current map in which a plurality of output values ​​of the drive system and a plurality of output current values ​​of the battery are mapped to set a reserve output current of the battery corresponding to the set output of the drive system, set an additional output current of the battery based on the predicted degree of energy loss, and set the sum of the reserve output current and the additional output current as the output current.

[0013] In a computing system according to one embodiment disclosed herein, the energy management unit can predict the temperature change of the battery based on the vehicle's driving data and the battery data of the battery contained in the vehicle, and can determine the change in the internal resistance of the battery based on the predicted temperature change.

[0014] In a computing system according to one embodiment disclosed in this document, the energy management unit can determine that the internal resistance increases when it determines that the temperature of the battery increases within a temperature range above the optimal temperature.

[0015] In a computing system according to one embodiment disclosed in this document, the energy management unit can determine that the internal resistance increases when it determines that the temperature of the battery decreases within a temperature range below the optimal temperature.

[0016] In a computing system according to one embodiment disclosed herein, the driving data may include data relating to at least one of the external temperature of the vehicle, the incline of the road on which the vehicle is traveling, the road surface condition, or the vehicle's behavior data.

[0017] In a computing system according to one embodiment disclosed in this document, the autonomous driving control unit can set the output of the drive system based on the driving data and the vehicle characteristic data.

[0018] In a computing system according to one embodiment disclosed in this document, the determined change in internal resistance can be a prediction of the internal resistance of the battery at a future point in time.

[0019] In a computing system according to one embodiment disclosed herein, the autonomous driving control unit can set the output of the drive system using a power map in which the driving data and the vehicle characteristic data are mapped to a plurality of output values ​​of the drive system.

[0020] A method for adjusting the operation of a vehicle battery according to one embodiment disclosed herein may include: receiving vehicle driving data and battery data of the battery; determining a change in the internal resistance of the battery based on the driving data and the battery data; and setting the output current of the battery for a set output of the vehicle's drive system based on the determined change in internal resistance.

[0021] A method for adjusting the operation of a vehicle battery according to one embodiment disclosed herein may further include an operation to determine the degree of energy loss due to the determined change in internal resistance, and an operation to set the output current based on the determined degree of energy loss.

[0022] A method for adjusting the operation of a vehicle battery according to one embodiment disclosed herein may further include setting the output current higher when the determined degree of energy loss increases.

[0023] A method for adjusting the operation of a vehicle battery according to one embodiment disclosed herein may further include: setting a reserve output current of the battery corresponding to the set output of the drive system using a current map which maps a plurality of output current values ​​of the drive system to a plurality of output current values ​​of the battery; setting an additional output current of the battery based on the predicted degree of energy loss; and setting the sum of the reserve output current and the additional output current as the output current.

[0024] The method for adjusting the operation of the vehicle battery according to an embodiment disclosed in this document can further include an operation of predicting the temperature change of the battery based on the driving data of the vehicle and the battery data of the battery included in the vehicle, and an operation of determining the change in the internal resistance of the battery based on the predicted temperature change.

[0025] The method for adjusting the operation of the vehicle battery according to an embodiment disclosed in this document can further include an operation of determining that the internal resistance increases when it is determined that the temperature of the battery increases within a temperature range above the optimum temperature.

[0026] The method for adjusting the operation of the vehicle battery according to an embodiment disclosed in this document can further include an operation of determining that the internal resistance increases when it is determined that the temperature of the battery decreases within a temperature range below the optimum temperature.

[0027] In the method for adjusting the operation of the vehicle battery according to an embodiment disclosed in this document, the driving data can include data related to at least one of the external temperature of the vehicle, the slope of the road on which the vehicle is traveling, the road surface condition, or the behavior data of the vehicle.

[0028] The method for adjusting the operation of the vehicle battery according to an embodiment disclosed in this document can further include an operation of setting the output of the drive system based on the driving data and the characteristic data of the vehicle.

[0029] The method for adjusting the operation of the vehicle battery according to an embodiment disclosed in this document can further include an operation of setting the output of the drive system using a power map in which the driving data, the characteristic data of the vehicle, and a plurality of output values of the drive system are mapped.

Advantages of the Invention

[0030] According to the embodiments disclosed in this document, it is possible to provide a computing system that can provide not only autonomous driving control but also energy management services based on battery data, and a vehicle including the same.

[0031] According to the embodiments disclosed in this document, the vehicle's energy efficiency can be improved by setting the battery output current in consideration of changes in the battery's internal resistance due to the vehicle's driving environment and / or driving conditions.

[0032] 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]

[0033] [Figure 1] This is a block diagram of a vehicle according to at least one embodiment of the present disclosure. [Figure 2] This is a diagram illustrating the operation of components included in a computing system according to at least one embodiment of the present disclosure. [Figure 3] This figure illustrates the optimal temperature of a battery according to at least one embodiment of the present disclosure. [Figure 4] This figure illustrates an example of how energy loss occurs due to an increase in the internal resistance of a battery according to at least one embodiment of the present disclosure. [Figure 5] This figure shows the output power of a battery according to at least one embodiment of the present disclosure. [Figure 6] This is a flowchart illustrating the operation of a computing system according to at least one embodiment of the present disclosure. [Figure 7] This is a flowchart illustrating the operation of a computing system according to at least one embodiment of the present disclosure. [Figure 8] This is a flowchart illustrating the operation of a computing system according to at least one embodiment of the present disclosure. [Modes for carrying out the invention]

[0034] 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.

[0035] 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.

[0036] 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).

[0037] 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).

[0038] 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.

[0039] 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.

[0040] Figure 1 is a block diagram of a vehicle according to one embodiment.

[0041] Referring to Figure 1, the vehicle 100 may include a communication module 110, a sensor module 120, a computing system 130, a battery 140, and a drive system 150. For example, the vehicle 100 may be an electric vehicle (EV) or a hybrid electric vehicle (HEV) that generates driving force using electrical energy. Furthermore, according to various embodiments, the vehicle 100 may include a vehicle with autonomous driving capabilities, and the communication module 110, sensor module 120, and computing system 130 may be implemented in the form of an autonomous driving platform, but are not limited thereto.

[0042] The communication module 110 can communicate with external electronic devices. For example, the communication module 110 can establish wired and / or wireless communication channels and exchange various data with external electronic devices via the established communication channels.

[0043] The sensor module 120 can detect objects located around the vehicle 100. For example, the sensor module 120 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.

[0044] The computing system 130 can comprehensively manage the operation of the vehicle 100 and the functions it provides. To this end, the computing system 130 can control and / or manage the operation of the communication module 110, the sensor module 120, the battery 140, and / or the drive system 150.

[0045] The computing system 130 can process a variety of calculations related to the vehicle 100 and can execute programs, software, or instructions. According to the embodiment, the computing system 130 can process calculations related to the driving control of the vehicle 100 and / or calculations related to energy management functions. For example, calculations related to the driving control of the vehicle 100 may include calculations for determining / deciding the driving strategy, driving path, behavior, etc., of the vehicle 100.

[0046] The computing system 130 can process calculations related to the driving control of the vehicle 100 and / or calculations related to energy management functions based on the driving data of the vehicle 100 and / or battery data indicating the state of the battery 140 (e.g., voltage data, current data, temperature data, and / or charge state data, SOC, SOH, cumulative charge current, cumulative discharge current, cumulative charge energy, cumulative discharge energy, insulation resistance, relay state data, etc.).

[0047] In a typical electric vehicle, the vehicle's controller processes 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 130 can be configured to process both calculations related to driving control and calculations related to energy management functions. With this configuration, the computing system 130, which has a relatively much higher processing power compared to the battery management module (e.g., the BMS 141 in Figure 2), can perform the energy management function, thus enabling more stable and smoother energy management of the vehicle 100.

[0048] Furthermore, some of the calculations related to the energy management function of the vehicle 100 can be processed by the computing system 130, and the remaining calculations can be processed by the management module of the battery 140. By distributing the calculations related to the energy management function to the computing system 130 and the battery 140 in this way, more stable and smoother energy management of the vehicle 100 can be achieved, and the management module provided in the battery 140 can be made less complex.

[0049] The computing system 130 may include at least one processor for arithmetic processing and instruction execution, and interface circuits for interacting with other elements of the vehicle 100. 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).

[0050] At least one processor of the computing system 130 may have a structure for executing instructions that realize processes to be processed inside the vehicle 100. At least one processor may be implemented as an array of numerous logic gates for processing various 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, a CPU (central processing unit), a GPU (graphics processor unit), an AP (application processor), an ASIC (application specific integrated process), or a combination thereof.

[0051] At least one processor of the computing system 130 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. In some embodiments, the computing system 130 is a system-on-chip (SoC).

[0052] The battery 140 can supply power and / or electrical energy to the vehicle 100. For example, the battery 140 may be a rechargeable secondary battery that is discharged while supplying power to the vehicle 100 and charged by a battery charger, and may, but is not limited to, a lithium-ion battery. According to some embodiments, the battery 140 may include battery cells, battery modules, battery packs, and / or battery racks.

[0053] The drive system 150 can control the driving and / or behavior of the vehicle 100. For example, it can control the operation of actuators related to braking, driving, and attitude of the vehicle 100. According to embodiments, the drive system 150 may include, but is not limited to, a braking system that controls the operation of actuators related to braking, an attitude control system that controls the operation of actuators for maintaining a stable attitude 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 driving speed of the vehicle.

[0054] According to the embodiment, the drive system 150 can control the driving and / or behavior of the vehicle 100 in response to control commands from the computing system 130. For example, the drive system 150 can control the driving and / or behavior of the vehicle 100 in response to control commands based on the calculation results of the computing system 130 (e.g., calculation / execution results of autonomous driving software).

[0055] The operation of a computing system according to some embodiments will be described below with reference to Figures 2 to 5.

[0056] Figure 2 is a diagram illustrating the operation of components included in a computing system according to some embodiments. Figure 3 is a diagram illustrating the optimal temperature of a battery according to some embodiments. Figure 4 is a diagram illustrating an example of energy loss occurring due to an increase in the internal resistance of a battery according to some embodiments. Figure 5 is a diagram showing the output power of a battery according to some embodiments.

[0057] Referring to Figure 2, the computing system 130 may include an autonomous driving control unit 131 and an energy management unit 132.

[0058] According to some embodiments, the autonomous driving control unit 131 can execute autonomous driving software that controls the autonomous driving of the vehicle 100. Here, the autonomous driving software may be stored in memory (not shown) included in the computing system 130. The operations of the autonomous driving control unit 131 described below may be operations performed by the autonomous driving control unit 131 executing the autonomous driving software.

[0059] According to some embodiments, the autonomous driving control unit 131 can acquire driving data of the vehicle 100 from at least one vehicle module (e.g., a communication module 110 and / or a sensor module 120). The driving data can include various data related to the driving of the vehicle 100 acquired by the communication module 110 and / or the sensor module 120. For example, the driving data can include object data and behavior data. Object data can include the type and number of surrounding objects, the distance to the vehicle 100, the position relative to the vehicle 100, the ground position, relative speed, ground speed, relative acceleration, ground acceleration, external temperature, the slope of the road during driving, the road surface condition, etc., while behavior data can include the position of the vehicle 100, the path traveled, the distance traveled, the speed, acceleration, steering angle, yaw, pitch, roll, etc.

[0060] According to some embodiments, the autonomous driving control unit 131 can control the drive system 150 based on driving data to perform driving control, including acceleration, deceleration, steering, and combinations thereof, for the autonomous driving of the vehicle 100.

[0061] According to some embodiments, the autonomous driving control unit 131 can set the output of the drive system 150 (e.g., a motor). According to some embodiments, the autonomous driving control unit 131 can set the output of the drive system 150 based on driving data and characteristic data of the vehicle 100. Here, the characteristic data of the vehicle 100 refers to data relating to characteristics that may be present depending on the type of vehicle 100 (e.g., weight, type of components, etc.).

[0062] According to some embodiments, the autonomous driving control unit 131 can set the output of the drive system 150 using a power map stored in memory (not shown). The power map can be a table in which driving data and characteristic data are mapped to multiple output values ​​of the drive system 150. Specifically, the power map can be a table in which multiple state information of multiple variables included in the driving data (e.g., external temperature, road gradient, road surface condition, vehicle speed 100) and multiple state information of multiple variables included in the characteristic data (e.g., weight, motor type) are mapped to multiple output values ​​of the drive system 150. For example, in the power map, the output value of the drive system 150 mapped when the external temperature is 35°C, the road gradient is 15%, and the vehicle speed 100 is 120 km / h may be X. The autonomous driving control unit 131 can set the output of the drive system 150 to X if the driving environment and conditions identified based on the driving data are as described above.

[0063] According to some embodiments, the autonomous driving control unit 131 can transmit the output of the drive system 150 to the energy management unit 132.

[0064] According to some embodiments, the autonomous driving control unit 131 can obtain battery data relating to the state of the battery 140 (e.g., voltage data, current data, temperature data, SOC (State of Charge), SOH (State of Health), cumulative charging current, cumulative discharging current, cumulative charging power, cumulative discharging power, insulation resistance, relay status data, etc.) from the BMS 141 included in the battery 140. Here, the battery 140 may include battery cells, battery modules, battery packs, and / or battery racks, and may include a BMS 141 for managing the battery cells, modules, packs, etc.

[0065] According to some embodiments, the BMS 141 can comprehensively manage the operation / function of the battery 140. According to some embodiments, the BMS 141 can process calculations related to energy management functions, and optionally, the BMS 141 can provide the results of these calculations to the computing system 130. For example, the BMS 141 can measure the voltage, current, temperature, etc., of the battery 140, and can estimate SOC, SOH, etc., to generate battery data. According to some embodiments, the estimation of SOC or SOH may be performed by the energy management unit 132 instead of the BMS 141.

[0066] According to some embodiments, the autonomous driving control unit 131 can control the drive system 150 by further considering battery data, thereby enabling driving control of the vehicle 100, including acceleration, deceleration, steering, and combinations thereof, for autonomous driving.

[0067] According to some embodiments, the autonomous driving control unit 131 can transmit battery data to the energy management unit 132.

[0068] According to some embodiments, the energy management unit 132 can provide a variety of energy management services related to the energy management of the vehicle 100 (e.g., battery status diagnosis, battery life prediction, battery operation control, battery charge / discharge control, etc.) by executing energy management software. For example, the energy management unit 132 can transmit energy management data generated by executing the energy management software to the autonomous driving control unit 131 and / or BMS 141. Here, the energy management software may be stored in memory (not shown) included in the computing system 130. The operations of the energy management unit 132 described below may be operations performed by the energy management unit 132 by executing the energy management software. The autonomous driving control unit 131 and / or the energy management unit 132 may be implemented by one or more computer programs executed on the computing system 130. For example, the autonomous driving control unit 131 and the energy management unit 132 may be separate programs executed by the computing system 130. In some embodiments, the autonomous driving control unit 131 and / or the energy management unit 132 can be executed by a processor of the computing system 130, another processor, and / or a processor such as an SoC.

[0069] According to some embodiments, the energy management unit 132 can acquire driving data and / or battery data from the autonomous driving control unit 131. According to some embodiments, the energy management unit 132 may acquire battery data directly from the BMS 141.

[0070] According to some embodiments, the energy management unit 132 can set the output current of the battery 140 for the output of the drive system 150 set by the autonomous driving control unit 131.

[0071] According to some embodiments, the energy management unit 132 can predict changes in the internal resistance of the battery 140 based on driving data and battery data.

[0072] Referring to Graph 300 in Figure 3, it can be seen that the internal resistance of battery 140 changes with the temperature of battery 140. According to Graph 300, in the temperature range below the optimal temperature (e.g., 25°C), the closer the temperature of battery 140 is to the optimal temperature (i.e., the higher the temperature), the lower the internal resistance of battery 140. Also, in the temperature range above the optimal temperature, the closer the temperature of battery 140 is to the optimal temperature (i.e., the lower the temperature), the lower the internal resistance of battery 140.

[0073] This is because, when the temperature of battery 140 decreases (or increases) below (or above) the optimal temperature, electrochemical abnormal reactions occurring inside battery 140 cause changes in lithium ions (e.g., decreased migration and / or disappearance). For example, when the temperature of battery 140 decreases below the optimal temperature, electrolyte decomposition, micro-side reactions, and cathode material surface reduction occurring inside battery 140 can decrease lithium ion migration and / or cause lithium ions to disappear, potentially increasing the internal resistance of battery 140. As another example, when the temperature of battery 140 increases above the optimal temperature, electrolyte decomposition and lithium ion deposition occurring inside battery 140 can decrease lithium ion migration and / or cause lithium ions to disappear, potentially increasing the internal resistance of battery 140.

[0074] Therefore, in order to predict the change in the internal resistance of the battery 140, it is necessary to predict the temperature change of the battery 140. Furthermore, in order to predict such a temperature change of the battery 140, it is important to understand in advance the effects on the temperature of the battery 140 from both the inside and outside of the vehicle 100.

[0075] Furthermore, referring to Figure 2, the energy management unit 132 can predict the temperature change of the battery 140 based on the driving data and battery data.

[0076] According to some embodiments, the energy management unit 132 can predict the temperature change of the battery 140 by considering the external temperature of the vehicle 100, the incline of the road on which the vehicle 100 is traveling, the road surface conditions, and / or the current output of the drive system 150. The external temperature of the vehicle 100 can cause the temperature of the battery 140 to rise as high heat from the atmosphere and road is conducted to the vehicle. The steeper the road incline or the more irregular the road surface conditions, the greater the gravitational and / or frictional forces acting on the vehicle 100, so that the output of the drive system 150 needs to be higher to maintain the same speed. Thus, the heat from the drive system 150 for high output, particularly from the rotation and friction of the motor, can be conducted to the battery 140, potentially raising the temperature of the battery 140. Therefore, the energy management unit 132 can predict that the temperature of the battery 140 will rise as the external temperature of the vehicle 100 rises, as the slope of the road increases, as the road surface conditions become more irregular, and / or as the current output of the drive system 150 increases.

[0077] According to some embodiments, the energy management unit 132 can predict a change in the internal resistance of the battery 140 based on the predicted temperature change of the battery 140. According to some embodiments, the energy management unit 132 can predict an increase in the internal resistance of the battery 140 if the temperature of the battery 140 is predicted to decrease within a temperature range below the optimal temperature. For example, the energy management unit 132 can predict an increase in the internal resistance of the battery 140 if the current temperature of the battery 140, identified based on battery data, is below the optimal temperature, and the temperature of the battery 140 is predicted to decrease based on driving data. According to some embodiments, the energy management unit 132 can predict an increase in the internal resistance of the battery 140 if the temperature of the battery 140 is predicted to increase within a temperature range above the optimal temperature. For example, the energy management unit 132 can predict an increase in the internal resistance of the battery 140 if the current temperature of the battery 140, identified based on battery data, is above the optimal temperature, and the temperature of the battery 140 is predicted to increase based on driving data.

[0078] According to some embodiments, the energy management unit 132 can predict the degree of energy loss due to the predicted change in the internal resistance of the battery 140. Below, with reference to Figure 4, the energy loss caused by an increase in the internal resistance of the battery 140 will be described.

[0079] Referring to the battery equivalent circuit diagram 410 in Figure 4, the internal resistance R1 of the battery 140 and the output current I from the voltage source V result in the heat loss energy P. heat1 This can occur. Therefore, the output energy P1 of battery 140 can be calculated by the following mathematical formula 1.

[0080] [Mathematical formula 1]

number

[0081] According to some embodiments, the internal resistance R2 of the battery equivalent circuit diagram 420 may have a greater resistance value than the internal resistance R1 of the battery equivalent circuit diagram 410. In this case, the heat loss energy P generated by the internal resistance R2 of the battery 140 and the output current I from the voltage source V. heat2 The heat loss energy P generated by the internal resistance R1 is heat1 It is greater than that. As a result, the output energy P2 of battery 140, calculated by the following mathematical formula 2, may be lower than the output energy P1.

[0082] [Mathematical formula 2]

number

[0083] Thus, when the internal resistance of battery 140 increases, the output energy of battery 140 may decrease due to the increased heat loss energy caused by the increased internal resistance. Therefore, when an increase in the internal resistance of battery 140 is predicted, it is necessary to prevent a decrease in the output energy of battery 140 by setting a higher output current for battery 140.

[0084] Referring further to Figure 2, the energy management unit 132 can predict the degree of energy loss due to changes in the internal resistance of the battery 140 and set the output current of the battery 140 based on the predicted degree of energy loss. For example, the greater the predicted degree of energy loss, the higher the output current of the battery 140 can be set by the energy management unit 132.

[0085] According to some embodiments, the energy management unit 132 can set the output current based on a preliminary output current of the battery 140 corresponding to the output of the drive system 150 and an additional output current of the battery 140 based on the predicted degree of energy loss. According to some embodiments, the energy management unit 132 can set the preliminary output current of the battery 140 corresponding to the output of the drive system 150 using a current map in which multiple output values ​​of the drive system 150 and multiple output current values ​​of the battery 140 are mapped. Here, the current map can be a table showing the theoretical output current of the battery 140 to produce a set output of the drive system 150 without considering driving data. According to some embodiments, the energy management unit 132 can set the additional output current of the battery 140 according to the predicted degree of energy loss. According to some embodiments, the output current of the battery 140 can be set by adding the preliminary output current and the additional output current.

[0086] Referring to Figure 5, we can see graph 510 showing the output power of battery 140 when the output current of battery 140 is set without considering the driving environment and / or driving conditions of vehicle 100, and graph 520 showing the output power of battery 140 when a computing system 130 according to some embodiments sets the output current of battery 140.

[0087] According to Graph 510, in the section where the vehicle 100's speed increases (the section from T1 to T2 or the section from T4 to T5), the output power of the battery 140 is set excessively high compared to the required power because it is difficult to grasp the energy loss caused by changes in internal resistance due to the driving environment. Subsequently, in the section where the vehicle 100's speed decreases (the section from T2 to T3 or the section from T5 to T6), the excessively high output power is reduced. In other words, if the output current of the battery 140 is set without considering the driving environment and / or driving conditions, inefficiencies may occur where the power used is excessively high compared to the required power, as shown in Graph 510.

[0088] According to Graph 520, the section in which the speed of vehicle 100 increases (the section from T7 to T8 or from T9 to T 10 In the section, the computing system 130 predicts the change in internal resistance considering the driving environment and / or driving conditions, and sets the output current of the battery 140 based on the predicted change in internal resistance, thereby setting the output power of the battery 140 to be similar to the required power. That is, by setting the output current of the battery 140 considering the driving environment and / or driving conditions, the power used becomes similar to the required power, as shown in Graph 520, and the energy efficiency of the vehicle 100 can be improved.

[0089] Figure 6 is a flowchart illustrating the operation of a computing system according to one embodiment. Figure 6 can be explained using the configurations shown in Figures 1 and 2.

[0090] The embodiment shown in Figure 6 is only one of several embodiments, and the order of steps in the various embodiments of the present invention may differ from that shown in Figure 6. Some of the steps shown in Figure 6 may be omitted, the order of the steps may be changed, or steps may be merged.

[0091] Referring to Figure 6, in operation 605, the computing system 130 can set the output of the drive system 150 (e.g., a motor). According to some embodiments, the computing system 130 can set the output of the drive system 150 based on driving data and vehicle characteristic data. Here, the vehicle characteristic data refers to data relating to the characteristics that may be present depending on the type of vehicle 100 (e.g., weight, type of components, etc.).

[0092] According to some embodiments, the computing system 130 can set the output of the drive system 150 using a power map stored in memory (not shown). The power map can be a table in which driving data and characteristic data are mapped to multiple output values ​​of the drive system 150. Specifically, the power map can be a table in which multiple state information of multiple variables included in the driving data (e.g., external temperature, road gradient, road surface condition, vehicle speed 100) and multiple state information of multiple variables included in the characteristic data (e.g., weight, motor type) are mapped to multiple output values ​​of the drive system 150. For example, in the power map, the output value of the drive system 150 mapped when the external temperature is 35°C, the road gradient is 15%, and the vehicle speed 100 is 120 km / h may be X. The computing system 130 can set the output of the drive system 150 to X if the driving environment and conditions identified based on the driving data are as described above.

[0093] In operation 610, the computing system 130 can predict changes in the internal resistance of the battery 140 based on driving data and battery data. For example, the computing system 130 can predict temperature changes of the battery 140 based on driving data and battery data, and predict changes in the internal resistance of the battery 140 based on the predicted temperature changes. Embodiments in which the computing system 130 predicts changes in the internal resistance of the battery 140 will be described in more detail with reference to Figure 7 below.

[0094] In operation 615, the computing system 130 can set the output current of the battery 140 for the output of the drive system 150 set in operation 605. For example, the computing system 130 can predict the degree of energy loss based on the change in the internal resistance of the battery 140 predicted in operation 610, and set the output current of the battery 140 based on the predicted degree of energy loss. Embodiments in which the computing system 130 sets the output current of the battery 140 will be described more specifically with reference to Figure 8 below. By setting the output current of the battery according to the predicted degree of energy loss, the battery output can be suitably set considering the current driving conditions of the vehicle, thereby eliminating the need to set a conservatively high level of power output that could waste battery energy.

[0095] Figure 7 is a flowchart illustrating the operation of a computing system according to one embodiment. Figure 7 can be explained using the configurations shown in Figures 1 and 2.

[0096] The embodiment shown in Figure 7 is only one of several embodiments, and the order of steps in the various embodiments of the present invention may differ from that shown in Figure 7. Some of the steps shown in Figure 7 may be omitted, the order of the steps may be changed, or steps may be merged.

[0097] Referring to Figure 7, in operation 705, the computing system 130 can predict the temperature change of the battery 140 based on the driving data and battery data.

[0098] According to some embodiments, the computing system 130 can predict the temperature change of the battery 140 by considering the external temperature of the vehicle 100, the incline of the road on which the vehicle 100 is traveling, the road surface conditions, and / or the current output of the drive system 150. The external temperature of the vehicle 100 can cause the temperature of the battery 140 to rise as high heat from the atmosphere and road is conducted to the vehicle. The steeper the incline of the road or the more irregular the road surface conditions, the greater the gravitational and / or frictional forces acting on the vehicle 100, so that the output of the drive system 150 needs to be higher to achieve the same speed. Thus, the heat from the drive system 150 for high output, in particular from the rotation and friction of the motor, can be conducted to the battery 140, potentially raising the temperature of the battery 140. Therefore, the computing system 130 can predict that the temperature of the battery 140 will rise as the external temperature of the vehicle 100 rises, as the slope of the road increases, as the road surface conditions become more irregular, and / or as the current output of the drive system 150 increases.

[0099] In operation 710, the computing system 130 can identify the range of temperature change of the battery 140 predicted in operation 705. For example, if the current temperature of the battery 140, identified based on battery data, is below the optimal temperature, and the temperature of the battery 140 is predicted to decrease based on driving data, the computing system 130 can identify that the range of temperature change of the battery 140 is below the optimal temperature. As another example, if the current temperature of the battery 140, identified based on battery data, is above the optimal temperature, and the temperature of the battery 140 is predicted to increase based on driving data, the computing system 130 can identify that the range of temperature change of the battery 140 is above the optimal temperature.

[0100] If operation 710 identifies that the temperature change range is above the optimal temperature, then in operation 715, the computing system 130 can identify whether operation 705 predicted an increase in the temperature of the battery 140.

[0101] If operation 715 identifies that an increase in the temperature of battery 140 is predicted ("YES"), then in operation 720, the computing system 130 can predict that an increase in the internal resistance of battery 140 is predicted.

[0102] If operation 715 identifies that a decrease in the temperature of battery 140 is predicted ("NO"), then in operation 725, the computing system 130 can predict that a decrease in the internal resistance of battery 140 is predicted.

[0103] If operation 710 identifies that the temperature change range is below the optimal temperature, then in operation 730, the computing system 130 can identify whether operation 705 predicted that the temperature of the battery 140 would decrease.

[0104] If it is identified in operation 730 that the temperature of battery 140 is predicted to decrease ("YES"), then in operation 720, the computing system 130 can predict that the internal resistance of battery 140 will increase.

[0105] If operation 730 identifies that a decrease in the temperature of battery 140 is predicted ("NO"), then in operation 725, computing system 130 can predict that the internal resistance of battery 140 will decrease.

[0106] Figure 8 is a flowchart illustrating the operation of a computing system according to one embodiment. Figure 8 can be explained using the configurations shown in Figures 1 and 2.

[0107] The embodiment shown in Figure 8 is only one of several embodiments, and the order of steps in the various embodiments of the present invention may differ from that shown in Figure 8. Some of the steps shown in Figure 8 may be omitted, the order of the steps may be changed, or steps may be merged.

[0108] Referring to Figure 8, in operation 805, the computing system 130 can set the reserve output current of the battery 140 corresponding to the output of the drive system 150 set in operation 605 of Figure 6. According to some embodiments, the computing system 130 can set the reserve output current of the battery 140 corresponding to the set output of the drive system 150 using a current map in which multiple output values ​​of the drive system 150 are mapped to multiple output current values ​​of the battery 140. Here, the current map can be a table showing the theoretical output current of the battery 140 to produce the set output of the drive system 150 without considering driving data.

[0109] In operation 810, the computing system 130 can predict the degree of energy loss due to the change in the internal resistance of the battery 140, as predicted in operation 610 of Figure 6.

[0110] In operation 815, the computing system 130 can set an additional output current for the battery 140 based on the degree of energy loss predicted in operation 810.

[0111] In operation 820, the computing system 130 can set the output current of the battery 140 by adding the reserve output current set in operation 805 and the additional output current set in operation 815.

[0112] 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.

[0113] 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.

Claims

1. An autonomous driving control unit that controls the autonomous driving of the vehicle, Includes an energy management unit that provides services related to the energy management of the aforementioned vehicle, The autonomous driving control unit sets the output of the drive system included in the vehicle, The aforementioned energy management unit, Based on the vehicle's driving data and the battery data of the battery contained in the vehicle, the change in the battery's internal resistance is determined. A computing system that sets the output current of the battery for the set output of the drive system based on the determined change in internal resistance.

2. The aforementioned energy management unit, The degree of energy loss due to the change in internal resistance determined above is then determined, The computing system according to claim 1, wherein the output current is set based on the degree of energy loss determined above.

3. The computing system according to claim 2, wherein the energy management unit sets the output current to a higher value when the determined degree of energy loss increases.

4. The aforementioned energy management unit, Using a current map in which multiple output values ​​of the drive system and multiple output current values ​​of the battery are mapped, the auxiliary output current of the battery corresponding to the set output of the drive system is set. Based on the determined degree of energy loss, the additional output current of the battery is set. The computing system according to claim 2, wherein the current obtained by adding the aforementioned reserve output current and the aforementioned additional output current is set as the output current.

5. The aforementioned energy management unit, Based on the vehicle's driving data and the battery data of the battery contained in the vehicle, the temperature change of the battery is predicted. The computing system according to claim 1, which determines the change in the internal resistance of the battery based on the predicted temperature change.

6. The aforementioned energy management unit, The computing system according to claim 5, wherein it is determined that the internal resistance increases when it is determined that the temperature of the battery increases within a temperature range above the optimal temperature.

7. The aforementioned energy management unit, The computing system according to claim 5, wherein it is determined that the internal resistance increases when it is determined that the temperature of the battery decreases within a temperature range below the optimal temperature.

8. The computing system according to claim 5, wherein the driving data includes data relating to at least one of the external temperature of the vehicle, the incline of the road on which the vehicle is driving, the road surface condition, or the behavior data of the vehicle.

9. The computing system according to any one of claims 1 to 8, wherein the autonomous driving control unit sets the output of the drive system based on the driving data and the vehicle characteristic data.

10. The computing system according to claim 9, wherein the autonomous driving control unit sets the output of the drive system using a power map which maps the driving data and the vehicle characteristic data to a plurality of output values ​​of the drive system.

11. The computing system according to any one of claims 1 to 8, wherein the determined change in internal resistance is a prediction of the internal resistance of the battery at a future point in time.

12. A method for adjusting the operation of a vehicle's battery, The operation of receiving the vehicle's driving data and the battery data of the battery, Based on the aforementioned driving data and battery data, the operation determines the change in the internal resistance of the battery, A method comprising the action of setting the output current of the battery for a set output of the vehicle's drive system based on the determined change in internal resistance.

13. The operation of determining the degree of energy loss due to the change in internal resistance determined above, The method according to claim 12, further comprising setting the output current based on the determined degree of energy loss.

14. The method according to claim 13, further comprising setting the output current to a higher value when the determined degree of energy loss increases.

15. An operation to set the auxiliary output current of the battery corresponding to the set output of the drive system, using a current map which maps the multiple output values ​​of the drive system to the multiple output current values ​​of the battery, Based on the determined degree of energy loss, the operation of setting the additional output current of the battery, The method according to claim 13, further comprising the operation of setting the current obtained by adding the preliminary output current and the additional output current as the output current.

16. Based on the vehicle's driving data and the battery data of the battery contained in the vehicle, the operation predicts the temperature change of the battery. The method according to claim 12, further comprising the operation of determining a change in the internal resistance of the battery based on the predicted temperature change.

17. The method according to claim 16, further comprising the operation of determining that the internal resistance increases when it is determined that the temperature of the battery increases within a temperature range above the optimal temperature.

18. The method according to claim 16, further comprising the operation of determining that the internal resistance increases when it is determined that the temperature of the battery decreases within a temperature range below the optimal temperature.

19. The method according to claim 16, wherein the driving data includes data relating to at least one of the external temperature of the vehicle, the incline of the road on which the vehicle is driving, the road surface condition of the road, or the behavior data of the vehicle.

20. The method according to claim 12, further comprising the operation of setting the output of the drive system based on the aforementioned driving data and the vehicle characteristic data.

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