Vehicle simulation method and system

Abstract

A simulation method for an electric vehicle (EV) includes receiving a request from a driver of the electric vehicle to run a simulation of the target vehicle on the electric vehicle, acquiring a plurality of configuration parameters for simulating a behavior of the target vehicle on the electric vehicle, the configuration parameters including at least information about the target vehicle (702, 704, 706, 710) and settings of the target vehicle (708) for the driver, acquiring a plurality of vehicle parameters (704) of the electric vehicle, the plurality of vehicle parameters including at least runtime parameters of the electric vehicle and driving conditions of the electric vehicle, and running a simulation process using a vehicle simulator model (400) to acquire one or more control parameters (740, 742, 746, 748, 750, 752) for controlling the electric vehicle to realize the behavior, actions, and / or characteristics of the target vehicle on the electric vehicle based on the plurality of vehicle parameters (704) and the plurality of configuration parameters. The vehicle simulator model (400) is a neural network.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicles (EVs), and more particularly, to a vehicle simulation method and system for simulating the target behavior of a target vehicle in an electric vehicle.

Background Art

[0002] Electric vehicles behave differently compared to internal combustion engine (ICE) vehicles. For example, unlike ICE vehicles, EVs do not need to maintain the engine speed within a limited range. As a result, EVs do not have a jagged torque-speed curve like ICE vehicles. In another example, while the driver of an EV can enjoy the quiet and fast acceleration of the electric motor, they may lose the enjoyment of hearing the gas engine roar or feeling the vibrations when a gas engine runs. Therefore, the drivers of EVs and ICE vehicles have different driving experiences, and these differences may prevent more conventional vehicle drivers from purchasing an EV.

Summary of the Invention

Problems to be Solved by the Invention

[0003] The disclosed method and system aim to solve one or more of the above problems and other problems.

Means for Solving the Problems

[0004] One aspect of the present disclosure provides a simulation method for electric vehicles (EVs). The method includes: receiving a request from an EV driver to run a simulation of a target vehicle on the EV; obtaining a plurality of configuration parameters for simulating the behavior of a target vehicle on the EV, including at least information about the target vehicle and settings for the target vehicle for the driver; obtaining a plurality of vehicle parameters of the EV, including at least runtime parameters and driving conditions for the EV; and running a simulation process using a vehicle simulator model to obtain one or more control parameters for controlling the EV to realize the behavior, actions, and / or characteristics of the target vehicle on the EV, based on the plurality of vehicle parameters and the plurality of configuration parameters. The vehicle simulator model is a neural network trained to reflect the relationships between the plurality of vehicle parameters and the plurality of configuration parameters and one or more control parameters.

[0005] Another aspect of the present disclosure provides a simulation system for electric vehicles (EVs). The simulation system includes a plurality of input devices that provide a plurality of vehicle parameters, a memory that stores program instructions, and a processor coupled to the memory and the plurality of input devices. When executing a program instruction, the processor receives a request from an EV driver to run a simulation of a target vehicle on an EV, obtains a plurality of configuration parameters for simulating the behavior of a target vehicle on an EV, including at least information about the target vehicle and settings for the target vehicle for the driver, obtains a plurality of vehicle parameters of the EV, including at least runtime parameters and driving conditions for the EV, and runs a simulation process using a vehicle simulator model to obtain one or more control parameters for controlling the EV to realize the behavior, actions, and / or characteristics of the target vehicle on an EV, based on the plurality of vehicle parameters and the plurality of configuration parameters. The vehicle simulator model is a neural network trained to reflect the relationships between the plurality of vehicle parameters and the plurality of configuration parameters and one or more control parameters.

[0006] Another aspect of the present invention provides an electric vehicle (EV). The electric vehicle comprises a wireless communication device for connecting to a cloud server and / or a mobile terminal carried by the driver of the electric vehicle, and an on-board computer system, the on-board computer system receiving a request from the driver of the electric vehicle to run a simulation of a target vehicle on the electric vehicle, obtaining a plurality of configuration parameters for simulating the behavior of a target vehicle on the electric vehicle, including at least information about the target vehicle and settings for the target vehicle for the driver, obtaining a plurality of vehicle parameters of the electric vehicle, including at least runtime parameters of the electric vehicle and driving conditions of the electric vehicle, and running the simulation process using a vehicle simulator model to obtain one or more control parameters for controlling the electric vehicle to realize the behavior, actions, and / or characteristics of the target vehicle on the electric vehicle based on the plurality of vehicle parameters and the plurality of configuration parameters. The vehicle simulator model is a neural network trained to reflect the relationships between the plurality of vehicle parameters and the plurality of configuration parameters and one or more control parameters.

[0007] Other aspects of this disclosure may be understood by those skilled in the art in light of the description, claims, and drawings of this disclosure.

[0008] To more clearly illustrate the technical solutions in embodiments of the present invention, the drawings used in the description of the disclosed embodiments are briefly described below. Other drawings may be derived from such drawings by those skilled in the art without creative effort and may be incorporated into this disclosure. [Brief explanation of the drawing]

[0009] [Figure 1] An exemplary operating environment incorporating specific embodiments of this disclosure is shown. [Figure 2] A block diagram of an exemplary electric vehicle (EV) according to an embodiment of this disclosure is shown. [Figure 3A] A block diagram of an exemplary computer system according to an embodiment of this disclosure is shown. [Figure 3B] A block diagram of an exemplary computer system according to an embodiment of this disclosure is shown. [Figure 4] A block diagram of an exemplary simulation system for an EV according to the embodiments of this disclosure is shown. [Figure 5A] A block diagram of an exemplary vehicle simulator model according to an embodiment of this disclosure is shown. [Figure 5B] A block diagram of an exemplary target profile according to an embodiment of this disclosure is shown. [Figure 5C] An exemplary block diagram of a driver profile according to the embodiments of this disclosure is shown. [Figure 6] A flowchart illustrating an exemplary in-vehicle simulation method for an EV according to the embodiments of this disclosure is shown. [Figure 7] This disclosure illustrates a specific application of the simulation system for EVs according to this embodiment. [Figure 8] A flowchart for performing a safety check according to the embodiments of this disclosure is shown. [Modes for carrying out the invention]

[0010] The technical solutions of the present invention will be described below with reference to the drawings. These embodiments are provided to enable a more complete understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art, and it should be understood that the present disclosure can be implemented in various forms and should not be limited to the embodiments described herein.

[0011] In embodiments of this disclosure, a phrase such as "A and B are connected" may include situations in which A and B are connected to each other and in contact with each other, or situations in which A and B are connected through another component and are not in direct contact with each other. Also, terms such as "first" and "second" are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0012] For most consumers, electric vehicles (EVs) are new and often offer EV drivers a new driving experience. Some drivers may find the EV driving experience interesting and exciting, while others may feel nostalgic for the driving experience of more conventional vehicles, particularly high-performance internal combustion engine (ICE) vehicles such as the Mercedes AMG® series. Therefore, for EVs with sufficient capabilities, an onboard simulation method may be provided to customize the EV driving experience by simulating specific ICE vehicle characteristics. In other words, according to this disclosure, an electric vehicle (EV) may provide a simulation system for simulating specific characteristics of the vehicle in question. Figure 1 shows an exemplary operating environment incorporating an embodiment specific to this disclosure.

[0013] As shown in Figure 1, the operating environment 100 may include an EV 110, a driver / user 120, a user terminal 130, a cloud server 140, and a communication network 150. Any number of EVs, users, user terminals, servers, and / or communication networks may be included, as well as other components. The EV 110 may include any vehicle that operates on battery power, such as a pure or hybrid electric vehicle, including automobiles, aircraft, or ships. For example, the EV 110 may include a battery pack for supplying power to the EV 110, a set of wheels, at least one electric motor coupled to the battery pack for supplying drive power to the set of wheels to drive the EV 110, a wireless communication device for connecting to a cloud server and / or a mobile terminal carried by the driver of the EV 110, and an on-board computer system for simulating the target vehicle on the EV 110. The wireless communication device also provides a wireless connection to the Internet for synchronizing profiles and reporting errors and logs. Driver 120 may drive EV110, EV110 may be owned by driver 120 or owned by someone else, and may only be driven by driver 120. User terminal 130 may include any portable user device, such as a smartphone, personal digital assistant (PDA), notebook, laptop, or a combination of vehicle equipment and user device such as Apple CarPlay®. User terminal 130 may include any portable terminal. Furthermore, user terminal 130 may be carried or owned by driver 120, or may be located in or as part of an in-vehicle display device or other input mechanism in EV110.

[0014] Furthermore, the communication network 150 may include any type of communication network, such as wired and / or wireless networks, for connecting the EV110 and / or user terminal 130 to the cloud or cloud server 140. The cloud server 140 may be provided by a commercial entity for managing, monitoring, maintaining, or inspecting the EV110, such as a sales agent or vehicle manufacturer, or a cloud service provider for EV-related services. The cloud server 140 may store certain data necessary for the simulation and may perform calculations offloaded from the EV110.

[0015] Figure 2 shows a block diagram of an exemplary electric vehicle (EV) according to an embodiment of the present invention. As shown in Figure 2, the EV110 may include various subsystems or components. Specifically, the EV110 may include a plurality of wheels 240, an electric motor 222, an accelerator pedal 208, a brake pedal 206, a differential 238, a battery pack 216, an on-board computer system 230, a motor controller 218, a steering wheel 228, a driver's seat 226, a dashboard 232, a sound system 234, and an actuator 236. The EV110 may also include a charger 202, a converter 214, a 12V battery 204, a sensor 210, a wireless transceiver 212, an antenna 242, a transmission 224, and an inverter 220, etc. Any number of these subsystems or components may be included, certain components may be removed, and other components may be included.

[0016] The in-vehicle computer system 230 can control various components of the EV110. The charger 202 can charge the battery pack 216 via a converter 214 for converting an alternating current (AC) or direct current (DC) input into a suitable charging source. The charger 202 may include an in-vehicle charger of the EV110. The in-vehicle charger may be a Level 1 charger that receives a 120V AC output from a wall outlet. The EV110 / battery pack 216 can also be charged by an external Level 2 or Level 3 charger that uses a high-voltage AC power source to charge the battery pack 216 more quickly than the in-vehicle charger.

[0017] In some embodiments, the battery pack 216 may include a battery thermal management system to heat the battery pack 216 when the temperature of the battery pack 216 falls below a predetermined low temperature threshold or to cool the battery pack 216 when the temperature of the battery pack 216 exceeds a predetermined high temperature threshold. The battery pack 216 operates more effectively when the temperature of the battery pack 216 is within a range between the predetermined low temperature threshold and the predetermined high temperature threshold.

[0018] The output of the battery pack 216 may be supplied to the motor controller 218 to control the electric motor 222. The output of the battery pack 216 may pass through an inverter 220. The inverter 220 can adjust the voltage of the battery pack 216 to a voltage suitable for driving the electric motor 222. The output of the electric motor 222 can drive the wheels 240 through a transmission 224 and a differential 238.

[0019] Furthermore, the electric motor 222 can include a stator and a rotor (not shown in FIG. 2). The stator is a fixed outer shell of the electric motor 222 attached to the chassis of the EV 110. The rotor is a rotating element that supplies torque to the transmission 224 of the EV 110. The transmission 224 of the EV 110 adjusts the rotational speed of the rotor before using the torque of the rotor to drive the differential 238 of the EV 110. The differential 238 of the EV 110 distributes torque to each wheel 240 according to a specific ratio suitable for driving conditions.

[0020] The EV 110 may include more than one electric motor 222. For example, the EV 110 may include two electric motors 222. One electric motor 222 drives the two front wheels 240, and another electric motor 222 drives the two rear wheels 240. In another example, the EV 110 may include four electric motors 222. Each of the four electric motors 222 drives each of the four wheels 240 respectively. If each wheel 240 is directly driven by one electric motor 222, the differential 238 can be removed. Tires (not shown) may be attached to each wheel 240.

[0021] Furthermore, an accelerator pedal 208 and a brake pedal 206 may be provided and positioned to accelerate and decelerate the EV110. A sensor 210 and an actuator 236 may be provided to facilitate acceleration and deceleration. For example, the sensor 210 can detect the positions of the accelerator pedal 208 and the brake pedal 206 and make their positions available to the onboard computer system 230. The onboard computer system 230 controls the electric motor 222 via the motor controller 218 and inverter 220 according to the positions of the accelerator pedal 208 and the brake pedal 206. The actuator 236 may be controlled by the onboard computer system 230 to dynamically adjust the suspension of the EV110 based on the state of the EV110. In some embodiments, the actuator 236 may be controlled by the onboard computer system 230 to adjust the stiffness of the accelerator pedal 208 and the brake pedal 206.

[0022] The EV110 may also use the sound system 234 and the dashboard 232 to provide certain vehicle interactions to an individual (e.g., the driver 120 or another passenger in the EV110). For example, in addition to playing music and radio channels, the sound system 234 may be controlled by the onboard computer system 230 to simulate engine sounds. The dashboard 232 may be controlled by the onboard computer system 230 to display certain information to an individual, including an image of the dashboard of another vehicle.

[0023] The 12V battery 204 may be used to provide auxiliary power to various components of the EV110, such as the onboard computer system 230, dashboard 232, sound system 234, sensor 210, actuator 236, wireless transceiver 212, and other control circuits.

[0024] The wireless transceiver 212 may be connected to the antenna 242. The wireless transceiver 212 can facilitate communication between the in-vehicle computer system 230, the cloud server 140, and the user terminal 130 as shown in Figure 1. The wireless transceiver 212 may include a cellular communication transceiver supporting 3G / 4G / 5G cellular communication for communication with the cloud server 140, and a Bluetooth® / Wi-Fi® transceiver for communication with the user terminal 130. Other wireless communication formats may also be used.

[0025] The EV110 may provide a driver 120 with a steering wheel 228 and a driver's seat 226 for driving the EV110. For example, the driver 120 of the EV110 sits in the driver's seat 226 and uses the steering wheel 228 to steer the EV110 in the direction of travel. In one embodiment, a speaker (subwoofer, not shown) may be located under the driver's seat 226 to reproduce simulated engine sounds to the driver 120, or to reproduce low-frequency sounds to simulate vibrations caused by a gas engine. The EV110 may also include a Global Positioning System (GPS) device (not shown) for detecting the EV110's current location. The current location may be used to determine local traffic / safety rules and regulations. Local traffic / safety rules and regulations are used when performing safety checks on the EV110's controls.

[0026] During operation, the on-board computer system 230 may obtain multiple configuration parameters from one or more of the following: the on-board computer system's memory storage, a cloud server, and a mobile terminal carried by the driver of the EV110. The on-board computer system 230 may perform various control functions for the EV110, and may also perform a simulation process to simulate specific vehicle behavior of another vehicle. When performing a simulation process, the on-board computer system may offload part or all of the simulation process to a cloud server to limit energy consumption in the EV110. Figure 3A shows a block diagram of an exemplary on-board computer system according to an embodiment of the present disclosure. As shown in Figure 3A, the computer system 300 may include an EV processor 304, memory 302, display screen 306, microphone / speaker 308, interface 310, sensor 312, actuator 314, and camera 316, etc. The computer system 300 may be the on-board computer system 230 shown in Figure 2. Certain devices may be omitted, and other devices may be included.

[0027] Memory 302 can store program instructions. When executed by processor 304, the program instructions execute an in-vehicle simulation method for the EV110. In some embodiments, memory 302 includes dynamic random access memory (DRAM), an embedded multimedia controller (e.MMC), low-power DRAM (LPDRAM), NOR flash memory, single-level cell (SLC) NAND flash memory, a solid-state drive (SSD), a universal flash storage (UFS) device, or a combination thereof.

[0028] In some embodiments, the processor 304 may be one or more hardware processors, microprocessors, and microcontrollers distributed across various parts of the EV. For example, the EV processor 304 may include a vehicle network processor dedicated to the in-vehicle network, a vision processor dedicated to vision processing, a radar processor dedicated to radar processing, an engine control processor, a graphics processing unit (GPU) for dashboard rendering, an audio digital signal processor (DSP) for audio processing, a communications processor for supporting wireless communication such as 5G mobile, an artificial intelligence processor for implementing neural networks, or a combination thereof. In some embodiments, to save costs, certain dedicated processors described above may not be present in the EV. Therefore, computing tasks that require a dedicated processor may be offloaded to a cloud server that returns results upon completion of the computing task. In some other embodiments, computing tasks may be offloaded to a cloud server to save power in the EV.

[0029] The computer system 300 may also include a display screen 306 and a microphone / speaker 308 for interacting with the user 120 of the computer system 300. The display screen 306 is part of a human-machine interface (HMI) to facilitate interaction between the driver 120 and the computer system 300. The HMI may include an infotainment system and instrument clusters. The display screen 306 may include any suitable type of computer display or electronic device display. For example, the display screen 306 may include an LCD (Liquid Crystal Display) display, an OLED (Organic Light Emitting Diode) display, or a combination thereof. The display screen 306 may also be a touch-controlled display screen. The display screen 306 may include a gesture sensor for detecting hand gestures of the individual (e.g., driver, passenger) 120 in front of the display screen 306. The display screen 306 may also include a haptic driver for providing haptic feedback. The display screen 306 may also include a head-up display (HUD) that provides information to the driver 120 at eye level. The display screen 306 may also include a transparent window display that uses a projector mounted inside the EV110 to project images onto a transparent film sandwiched between or laminated in the windows of the EV110. A microphone / speaker 308 allows the individual to interact with the computer system 300 using voice commands. The microphone / speaker 308 may include an active noise cancellation function. The computer system 300 may also include other peripherals for interacting with the individual.

[0030] The computer system 300 may use interface 310 to connect various accessories such as sensors 312, actuators 314, and cameras 316. Interface 310 may include a vehicle interface processor (VIP). Sensors 312 and actuators 314 may also be sensors 210 and actuators 236 shown in Figure 2. The computer system 300 may include an internal bus for connecting memory 302, an EV processor 304, a display screen 306, a microphone / speaker 308, and interface 310 together. Interface 310 may be connected to sensors 312, actuators 314, and cameras 316 via the internal bus. For example, the internal bus may be a Controller Area Network (CAN) bus, a FlexRay bus, a Media-Oriented System Transport (MOST) bus, an Automotive Ethernet® bus, a Local Interconnection Network (LIN) bus, or a combination thereof. The internal bus may also be used to connect other accessories not shown in Figure 3A.

[0031] Returning to Figure 1, during operation, the user terminal 130 and / or the cloud server 140 may interact with the EV 110 or the in-vehicle computer system 230 via the communication network 150 to execute specific user processes or server processes. Figure 3B shows a block diagram of an exemplary computer system according to an embodiment of this disclosure. The computer system 350 may be the cloud server 140 shown in Figure 1.

[0032] As shown in Figure 3B, the computer system 350 may include memory 352, a processor 354, a communication interface 358, an input / output device 360, and a data storage device 362, etc. Other devices may also be included. The processor 354 may include any suitable hardware processor or multiple hardware processors. Furthermore, the processor 354 may include multiple cores for multithreading or parallel processing and may include graphics performance for processing for a human-machine interface (HMI) (i.e., an example of the input / output device 360). The memory 352 may include any suitable memory module such as ROM, RAM, flash memory modules, erasable and rewritable memory, as well as mass storage devices such as CD-ROM, DVD, U-disk, and hard disk. When executed by the processor 354, the memory 352 may store computer program instructions or program modules for implementing various processes in order to perform interaction with the in-vehicle computer system 230 on the EV110.

[0033] Furthermore, the computer system 350 may include a display device. The display device may be any suitable display technology suitable for displaying images or videos. For example, the display device may include a liquid crystal display (LCD) screen, an organic light-emitting diode (OLED) screen, or a touch screen. The communication interface 358 may include a specific network interface device for establishing a connection via a communication network. The input / output device 360 ​​may include any suitable input device for inputting information to the processor 354, such as a keypad, keyboard, and mouse device, camera, microphone, and other sensors, and / or output device for outputting information from the processor 354. Furthermore, the data storage device 362 may include one or more data storage devices for storing specific data and for performing specific operations on the stored data, such as database retrieval and model training. Because the memory size of the in-vehicle computer system 230 is limited, the data required for the simulation may be stored in the data storage device 362. If necessary, the data for the simulation may be downloaded from the data storage device 362 by the in-vehicle computer system 230. Furthermore, local regulations and / or rules may prevent data from being transmitted from EV110 without specific restrictions. Data may be tokenized, encrypted, and purged before being transmitted to the cloud server 140. Personally identifiable information must be protected whether it is stored in the in-vehicle computer system 230 or transmitted to the cloud server 140. In either case, data processing must be in accordance with the driver's consent or a service agreement signed by the driver.

[0034] In some embodiments, local regulations and / or rules may restrict the data collected by and transmitted from EVs. Data collected by and transmitted from EVs may be tokenized, encrypted, and purged so that personally identifiable information (PII) data is handled appropriately. Data collected by and transmitted from EVs are processed, used, and stored in accordance with the driver's consent and preferences.

[0035] Returning to Figure 1, during operation, the EV110 may be driven by a driver 120. After the driver 120 has entered the EV110, the driver 120 may interact with the EV110's onboard computer system 230 and provide inputs to the onboard computer system 230, thereby allowing the onboard computer system 230 to perform a simulation process to simulate specific vehicle behaviors, actions, and / or characteristics of the target vehicle on the EV110. The inputs may include user information and / or configuration information. As used herein, the term “simulate” may refer to the process of obtaining static and / or dynamic parameters of the EV110 to realize certain vehicle behaviors, actions, and / or characteristics of the target vehicle on the EV110, and safely controlling the EV110 to realize specific vehicle behaviors, actions, and / or characteristics of the target vehicle.

[0036] For example, the subject behavior of the subject vehicle may include the vehicle's handling characteristics, gear shifts, dynamic engine noise and vibrations transmitted to the driver's seat, the simulated dashboard of the subject vehicle, and combinations thereof. The vehicle's handling characteristics reflect how the vehicle responds to driver input and may include at least the vehicle's weight distribution and the cornering stiffness of the vehicle's tires. The vehicle's weight distribution may include the height of the center of gravity, the center of gravity, roll angle inertia, and yaw and pitch angle inertia. Other factors contributing to the vehicle's handling characteristics include the stiffness of the vehicle frame, electronic stability control, steering precision, power transmission to the wheels, braking effect, vehicle body aerodynamics, and vehicle suspension spring constants.

[0037] In internal combustion engine (ICE) vehicles, gasoline is burned to generate mechanical motion that moves the ICE vehicle, and gear shifts are used to adapt the vehicle's transmission to various vehicle speeds. Gear shifts in ICE vehicles cause abrupt changes in torque. Unlike ICE vehicles, electric vehicles (EVs) use one or more electric motors to drive the EV's wheels. One or more electric motors can be electrically controlled to drive the EV's wheels at various vehicle speeds without requiring gear shifts. Recreating gear shifts that cause abrupt changes in torque is one form of simulating the behavior of the vehicle in question.

[0038] Furthermore, the gasoline engines in ICE vehicles generate significant noise and vibration during operation. In contrast, one or more electric motors in an EV do not generate significant noise or vibration. To simulate the behavior of the target vehicle, it may be necessary for the EV to reproduce dynamic engine noise and vibration, which may be limited to the space surrounding the driver's seat.

[0039] The target vehicle does not necessarily have to be an ICE vehicle; a different EV or other type of vehicle may also be the target vehicle simulated on EV110. In another aspect of the simulation, different vehicles often have different dashboards. The simulation of the target vehicle's behavior may include recreating the target vehicle's dashboard. If the EV may include one or more display screens in the dashboard location, the EV controls one or more display screens to render the target vehicle's dashboard. For example, if the target vehicle is a different EV, the simulated dashboard of the other EV may be displayed on the EV so that the driver 120 has the feeling of being in a different EV when looking at the dashboard.

[0040] In some embodiments, it is necessary to display critical information specific to the EV (i.e., remaining battery charge). When the simulation is running, this critical information may be displayed in the EV's original format or in a different format. In addition, by facilitating dashboard customization, the driver may be able to view certain information that may not have been available on the vehicle's display (i.e., navigation information).

[0041] Various other behaviors, actions, and / or characteristics of the target vehicle may be simulated on the EV110. The simulation process may be implemented as simulation software that runs on the in-vehicle computer system 230, or on both the in-vehicle computer system 230 and the cloud server 140, or as a combination of software and hardware implemented by the in-vehicle computer system 230 and / or the cloud server 140. That is, the in-vehicle computer system 230 and / or the cloud server 140 may implement the simulation system on the EV110 and execute the simulation process based on the request of the driver 120. Figure 4 shows a block diagram of an exemplary simulation system for an EV according to an embodiment of this disclosure.

[0042] As shown in Figure 4, the simulation system 400 may include a simulator 402, a plurality of input modules 410, a plurality of output modules 420, and a plurality of action modules 430, among others. Other modules may also be included. The simulator 402 may include any suitable mathematical model or algorithm for generating specific simulation output parameters based on input parameters. Figure 5A shows a block diagram of an exemplary vehicle simulator model according to an embodiment of the present disclosure.

[0043] In some embodiments, the simulator 402 may include the neural network model 500 shown in Figure 5A. Hereinafter, the neural network model 500 is also referred to as the vehicle simulator model. The vehicle simulator model is trained to reflect the relationships between multiple vehicle parameters and multiple configuration parameters as inputs and one or more control parameters as outputs. Other types of artificial intelligence / machine learning models may also be used. The neural network model 500 may be a deep learning network model or a combination of multiple machine learning models, and may include an input layer 504, hidden layers 506, 508 (hidden layers), and an output layer 510, etc. If a convolutional neural network is included, the hidden layers may include convolutional layers. Furthermore, the input 502 may be provided to the input layer 504, and the output 512 may be provided by the output layer 510. Each layer may include one or more neural network nodes. The number of neural network layers is used for illustrative purposes, and any number of neural network layers may be used. The parameters of the neural network model 500 may be obtained by the in-vehicle computer system 230 or stored / transferred from the cloud server 140.

[0044] The neural network model 500 may be initially trained by the cloud server 140 to establish the simulator 402, for example. For example, the cloud server 140 may acquire historical data of the target vehicle (e.g., a vehicle of the same type as the target vehicle) and the EV 110 as input 502 and output 512 values ​​to train the neural network model 500. The cloud server 140 may also acquire operating vehicle data and driver 120 data to train the neural network model 500. For example, the vehicle data may include usage statistics such as simulation period (duration of simulation), location (vehicle position during simulation), and activation frequency, as well as error logs such as when the simulator 402 fails to initialize or is stopped (deactivated) by the safety module shown in Figure 4 during operation. In some embodiments, the cloud server 140 may extract only a portion of the vehicle data that can be used to train the vehicle simulator model. In this way, the amount of data collected can be reduced, saving energy in the EV and minimizing the use of the communication network. In some embodiments, local regulations and rules may restrict which data is permitted to be transmitted from the EV, so data extraction by the cloud server 140 may be restricted or require prior consent from an authorized person over the EV (e.g., the owner).

[0045] For example, in some embodiments, input 502 may include several vehicle parameters of the EV, including runtime parameters of the EV. Runtime parameters of the EV may be parameters that describe or affect the behavior of the vehicle during runtime (while driving), and runtime behavior may refer to the state in which the vehicle is driving. For example, runtime parameters of the EV may include at least steering wheel position, vehicle weight distribution, road surface conditions, impact distribution, brake position, torque vector, and battery availability, and output 512 may include one or more control parameters, including target turning angle, target steering ratio, target weight distribution, and target wheelbase. Input 502 may further include driving conditions of the EV. For example, driving conditions of the EV may include at least the position of the EV, data from the EV's sensors (e.g., rain / fog sensors), and camera feeds for understanding the terrain. Input 502 may further include local regulations and rules.

[0046] In another embodiment, input 502 may include several vehicle parameters of the EV, including accelerator pedal position, steering wheel position, road surface condition, confirmed traction force, available power, motor temperature, battery temperature, gyro measurement, accelerator measurement, suspension position, throttle position, brake position, and regenerative setting, and output 512 may include one or more control parameters, including target acceleration or deceleration, target drive wheel, target traction force setting, and target handling characteristics.

[0047] In another embodiment, input 502 may include several vehicle parameters of the EV, including accelerator pedal position and window position, and output 512 may include one or more control parameters, including at least one target engine sound on the driver side of the EV110. All suitable input and output parameters can be used.

[0048] After the neural network model 500 has been trained, it may be loaded into the EV110's in-vehicle computer system 230, for example, by retrieving it from the cloud server 140 via the communication network 150, or by locally storing the model data on the EV110.

[0049] Returning to Figure 4, the multiple input modules 410 may include several modules configured to provide input parameters based on specific types of input parameters. Specifically, the multiple input modules 410 may include a vehicle input module 412, a configuration module 414, and a safety module 416. Other modules may also be included.

[0050] The vehicle input module 412 may provide input parameters related to the vehicle itself, i.e., the EV110 or the host vehicle. That is, the vehicle input module 412 may provide values ​​for multiple vehicle parameters of the EV110. These multiple vehicle parameters may include torque parameters, weight distribution, steering parameters, acceleration and deceleration parameters, and suspension parameters.

[0051] Torque (pounds-feet or Newton-meters) is the amount of traction force generated by the electric motor 222 while the driver 120 of the EV110 is pressing the accelerator pedal 208. Horsepower refers to the power generated by the electric motor 222. Weight distribution is the amount of total vehicle weight on the ground at the axle, axle group, or individual wheels. Weight distribution affects how quickly a vehicle accelerates and decelerates, and how well it handles oncoming traffic. This is because the weight transfer that occurs when a vehicle is moving affects the level of tire grip.

[0052] Steering parameters include steering wheel position, brake pedal position, shock position, vehicle weight distribution, torque vector, road surface conditions, battery availability, or a combination thereof. Acceleration and deceleration parameters include steering position, road surface conditions, confirmed traction force, available power, motor temperature, battery pack temperature, gyro measurement, accelerator measurement, suspension position, throttle position, brake pedal position, regenerative settings, or a combination thereof. Some parameters may appear in two or more of the steering parameters, acceleration and deceleration parameters, and suspension parameters. Other parameters may also be included. Furthermore, the vehicle input module 412 may provide vehicle parameters in real time during operation. Alternatively, the vehicle input module 412 may provide stored vehicle parameters.

[0053] Furthermore, the configuration module 414 may provide the configuration of the simulation, i.e., input parameters related to the behavior of the target vehicle. That is, the configuration module 414 may provide values ​​for multiple target vehicle parameters and / or information about the driver, i.e., multiple configuration parameters. The multiple configuration parameters include at least information about the target vehicle and settings for the target vehicle for the driver. For example, the configuration module 414 may obtain the target profile of the target vehicle and / or the driver profile of the driver of the EV110 and determine the multiple configuration parameters for the simulation. Other information may also be included.

[0054] The target profile may include information for configuring the simulation. Figure 5B shows a block diagram of an exemplary target profile according to an embodiment of the present disclosure. As shown in Figure 5B, the target profile 550 may include vehicle manufacturer 552, vehicle model 554, vehicle behavior list 556, host vehicle requirements 558, simulator information 560, driver information 562, and other information 564. Certain information items are optional, and other information items may be added.

[0055] Vehicle manufacturer 552 may indicate the manufacturer of the vehicle in question, and vehicle model 554 may indicate the model of the vehicle in question. Vehicle behavior list 556 may indicate one or more vehicle behaviors or parameters to be simulated. For example, the subject profile of the vehicle in question may include horsepower / torque curves, suspension constants / types / programming, steering ratio, wheelbase, vehicle type, speed-fuel consumption curves, dashboard data, steering control weights, accelerator pedal feel and brake pedal feel, and braking characteristic values, or a combination thereof.

[0056] In the case of an ICE vehicle, torque is equal to the horsepower multiplied by a constant (e.g., 5,252) and divided by the rotational speed (revolutions per minute, or RPM). Due to gear shifts, the torque time curve of an ICE vehicle appears as a sawtooth curve. When the driver of an ICE vehicle presses the gas pedal, the torque increases over time, and then drops sharply when a gear shift occurs. Unlike ICE vehicles, EVs do not require gear shifts, and the torque-time curve initially rises and remains constant as long as the EV driver 120 continues to press the accelerator pedal 208. EVs and ICE vehicles behave substantially differently in response to the driver pressing the accelerator pedal or gas pedal. The gear shift behavior of an ICE vehicle is simulated by the onboard computer system 230 of the EV 110 to make the driver 120 of the EV 110 feel the gear shift behavior of an ICE vehicle.

[0057] The suspension may include an active suspension of the subject vehicle that controls the vertical motion of the subject vehicle's wheels relative to the subject vehicle's chassis or body, or a passive suspension provided by large springs whose vertical motion is entirely determined by the road surface. The active suspension may vary the stiffness of the shock absorbers to adapt to changing road or dynamic conditions, or it may use actuators to raise and lower the chassis independently at each wheel. The suspension may be a spring suspension, and the suspension constant may be called the spring constant. The spring constant is a component in setting the vehicle's ride height. When a spring is compressed or stretched, the force exerted by the spring is proportional to the change in its length. The spring constant is the change in the force exerted by the spring divided by the change in the spring's deflection. The spring constant may be programmed to adapt to the vehicle's weight. Therefore, the behavior of the subject vehicle's suspension needs to be simulated on the EV110.

[0058] The steering ratio refers to the ratio of the steering wheel's rotation angle to the wheel's rotation angle. A high steering ratio means that the steering wheel needs to be rotated more to turn the wheels, but it is easier to rotate the steering wheel. A low steering ratio means that the steering wheel needs to be rotated less to turn the wheels, but it is more difficult to rotate the steering wheel. Therefore, the steering wheel behavior of the vehicle in question needs to be simulated on the EV110.

[0059] The wheelbase is the horizontal distance between the centers of the front and rear wheels. When a vehicle accelerates, the suspension often causes the rear of the vehicle to sink and the front to lift. When a vehicle decelerates, the suspension often causes the rear of the vehicle to lift and the front to sink. The relative rise and fall of the front and rear of the vehicle, as well as the wheelbase, both affect the vehicle's weight distribution and the feeling of driving it. Therefore, the wheelbase behavior of the vehicle in question needs to be simulated on EV110.

[0060] Vehicle types may include sedan and sport utility vehicle (SUV) types. The vehicle type influences the feeling of driving the vehicle and plays a role in simulating the behavior of the target vehicle on EV110. The speed-fuel consumption curve is used to estimate the fuel consumption of the target vehicle. When driver 120 is driving EV110 operating in simulation mode, the estimated fuel consumption of the target vehicle may be displayed on the dashboard.

[0061] Dashboard data refers to data displayed on the dashboard of the target vehicle. Certain dashboard data from the target vehicle may no longer be applicable to the EV110, but it is still estimated and presented to the driver 120 on the EV110's dashboard, resulting in the EV110 driver 120 feeling as if they are driving the target vehicle. These steering control weights are used in four-wheel steering to improve turning agility and stability at various vehicle speeds. When the driver 120 turns the steering wheel at low speed, the front wheels rotate in the direction of travel and the rear wheels rotate in the opposite direction, effectively reducing the vehicle's turning radius and making low-speed maneuvering quicker and easier. Steering at high speeds causes both the front and rear wheels to rotate in the same direction to enhance high-speed stability. This steering behavior of the target vehicle may be simulated on the EV110. For certain ICE profiles, high-speed four-wheel steering behavior may be disabled. For example, four-wheel steering may be disabled for safety reasons if the EV's speed exceeds a predetermined speed threshold.

[0062] The feel of the accelerator pedal and brake pedal varies from vehicle to vehicle. Drivers often remember the feel of the accelerator pedal and brake pedal of the target vehicle. The feel of the accelerator pedal and brake pedal of the target vehicle needs to be simulated on EV110. Braking characteristics include braking distance or stopping distance. Braking distance is the distance the vehicle travels from the moment the brake pedal is pressed until the vehicle comes to a complete stop. Braking distance is mainly influenced by vehicle speed and the coefficient of friction between the tires and the road surface. The braking characteristics of the target vehicle need to be simulated on EV110. Furthermore, for safety reasons, the EV's maximum braking capacity is always available in the event of an emergency. Emergencies may include, but are not limited to, a tire puncture, headlight failure, throttle / accelerator sticking, engine stall, impending collision, road wildlife, and veering off the road.

[0063] Furthermore, as shown in Figure 5B, the host vehicle requirements 558 may specify one or more requirements for the host vehicle to perform the simulation, such as horsepower and powertrain configuration. Simulator information 560 may specify information specific to the simulator for simulating the target vehicle, and driver information 562 may be used to identify the target profile when searching for and identifying the target profile using driver identification information. Other information 564 may be used for other user or vehicle-specific information.

[0064] Furthermore, the driver profile may include information about driver 120 in particular to facilitate the simulation process. Figure 5C shows a block diagram of an exemplary driver profile according to an embodiment of the present disclosure. As shown in Figure 5C, the driver profile 580 may include driver identification 582, driver personal information 584, driver vehicle information 586, driver account information 588, driver social media information 590, target profile list 592, and other information 594. Certain information items are optional, and other information items may be added.

[0065] Driver identification 582 may indicate the identification of driver 120, which may be used to search the data storage device. Driver personal information 584 may include personal information about driver 120, such as weight, gender, age, address, location, and occupation. Driver vehicle information 586 may include vehicle-specific information of the driver, such as vehicle registration, vehicle garage information, and vehicle usage information. Driver account information 588 may include login information for accessing the cloud server 140, and driver social media information 590 may include information about the driver's social network presence, such as the driver's social media access information for sharing recorded trip data. Recorded trip data may include simulation data, which includes information about the selected ICE profile. Simulation data within recorded trip data shared by the driver on social media may be used as a training dataset for training a vehicle simulator model. The target profile list 592 may include one or more target profiles that the driver can use or select to run the simulation, each of which may be individually selected by the driver 120 to simulate the behavior of the target vehicle on the EV 110. Other information 594 may include information specific to other applications.

[0066] Returning to Figure 4, the input module 410 may also include a safety module 416. The safety module 416 may provide information for performing safety checks during the simulation process to ensure that the simulation is safe and conforms to certain rules and regulations. For example, the safety module 416 may include range information for configuration parameters so that range information can be used for safety checks on configuration parameters to ensure that the values ​​of the configuration parameters are within a safe range. The safety module 416 may also include range information for output parameters and / or action parameters so that range information can be used for safety checks on output parameters and / or action parameters to ensure that the values ​​of output parameters and / or action parameters are within a safe range.

[0067] Furthermore, the safety module 416 may include regulatory information so that it can be used for safety checks on output parameters and / or action parameters to ensure that the values ​​of output parameters and / or action parameters comply with regulations, with or without location information. The safety module 416 may include specific system patches or update information so that simulator 402 and other modules can be updated or patched using system patches or update information. The safety module 416 may also include host vehicle requirements such as engine fault codes, overdue maintenance deadlines, and low tire pressure. The safety module 416 may also include other requirements or other information such as road terrain, local regulations and / or rules, and weather conditions.

[0068] Figure 8 shows a flowchart illustrating the execution of a safety check according to an embodiment of the present disclosure. The vehicle safety system may be the safety module 416 in Figure 4, and the simulator may be the simulator 402 in Figure 4. The vehicle safety system may further include an electronic control system, a telematics control system, and a driver assistance system. A pre-check is performed after receiving a driver request to start (activate) the simulator. The pre-check may include a safety check performed by the safety module 416 before the simulator 402 is started. If the EV110 passes the pre-check, the simulator 402 is started. If the EV110 fails the pre-check, the simulator 402 remains stopped (inactive). Alternatively, after the simulator 402 has been started, a driver request to stop the simulator 402 may be received. Upon receiving a driver request to stop the simulator 402, the simulator 402 is controlled to stop (deactivate). Alternatively, after the simulator 402 has been started, a fault may be detected by the safety module 416 (i.e., the vehicle safety system). In this way, failures are continuously monitored. If a failure is detected by the safety module 416, the simulator 402 is shut down.

[0069] In some embodiments, the pre-check may include the health (healthy condition) of the EV110. For example, health may include engine fault codes, overdue maintenance deadlines, and low tire pressure. The pre-check may also include restrictions imposed by local traffic / safety rules and regulations. For example, a road may be EV-only and ICE vehicles may not be permitted. The pre-check may also include ambient information from driver assistance systems. For example, unfavorable weather conditions may prevent the EV from entering simulation mode.

[0070] In some embodiments, a fault detected by the safety module 416 may include the value of a configuration parameter input to the simulator 402 being outside a predetermined safety range, and / or output parameters and / or action parameters output from the simulator 402 being outside a predetermined safety range. In some embodiments, a fault may include the EV moving from one area that permits the simulation mode to another area that prohibits the simulation mode. In this case, the EV's location is continuously monitored and corresponding local traffic / safety rules and regulations are verified. In some embodiments, a fault may also include unfavorable traffic conditions surrounding the EV. For example, the EV encounters congested traffic and is forced to move significantly slower than the road's speed limit. In some embodiments, a fault may also include the battery charge falling below a certain threshold. In this case, the EV needs to exit the simulation mode to conserve energy.

[0071] Furthermore, as shown in Figure 4, the multiple output modules 420 may include a look-and-feel module 422, a target dynamic module 424, and a data module 426, among others. Other modules may also be included. The look-and-feel module 422 may receive output parameters from the simulator 402 that are static and / or related to the look-and-feel of the target vehicle, such as the dashboard display, the light display, and the position and attitude of the driver's seat and steering wheel. In other words, all data relating to the appearance and feel of the target vehicle, i.e., the sound of the vehicle, the appearance of the vehicle, the display of the display, etc.

[0072] The target dynamic module 424 may receive output parameters from the simulator 402 that are dynamic and require the execution of specific sequential actions on the EV110 in order to change the driving characteristics of the EV110. This includes all data related to runtime vehicle behavior, such as acceleration or deceleration. When an action is required to achieve the target behavior, the target dynamic module 424 may provide information to the reproduction module 432 to trigger a change in vehicle behavior to satisfy the target profile of the driver 120.

[0073] Furthermore, the data module 426 may record simulation data from the simulator 402 and store the data or upload the data to the cloud server 140 in order to further train the vehicle simulator model in the simulator 402. For example, the data module 426 may record trip data and share the trip data via social media or other networks under the simulated scenario. That is, the driver 120 can use the data module 426 to share driving data of the virtual vehicle (i.e., the simulated target vehicle) on social media. In some embodiments, heatmaps can be introduced to reduce the size of input data from the EV and other sources, thereby allowing the trip data to be cleaned up (purged) to identify / remove all noise irrelevant to the trip.

[0074] Furthermore, as shown in Figure 4, the multiple action modules 430 may include a reproduction module 432, a vehicle control / display / voice module 434, a vehicle powertrain module 436, and a vehicle data analysis module 438, among others. Other modules may also be included. The reproduction module 432 may be provided to perform actions necessary to achieve the target behavior of the target vehicle. That is, the reproduction module 432 may receive information from the target dynamic module 424, determine one or more actions necessary to achieve the target behavior, and further instruct each module to perform the actions related to it.

[0075] For example, the vehicle control / display / voice module 434 can perform actions that fall into the categories of control, display, and voice; the vehicle powertrain module 436 can perform actions related to the powertrain; the vehicle data analysis module 438 can collect all action data and further anonymize the collected data, resulting in anonymized driving data (anonymized vehicle data) that can be uploaded to the cloud server 140 for analysis and / or vehicle simulator model training. For example, the collected data may include usage statistics such as simulation period, location, and startup frequency, as well as error logs such as when the simulator 402 fails to initialize or is stopped by the safety module 416 during operation.

[0076] During operation, the simulation system 400 or the in-vehicle computer system 230 interacts with the driver 120 to perform various simulation processes provided by the simulation system 400. Figure 6 shows an exemplary simulation process 600 according to an embodiment of the present disclosure.

[0077] As shown in Figure 6, in S602, the on-board computer system 230 may receive requests from the EV driver to simulate the behavior of the target vehicle on the EV. For example, the driver 120 can interact with the on-board computer system 230 to input simulation requests and also provide the on-board computer system 230 with a driver profile. The interaction between the driver 120 and the on-board computer system 230 may be in various ways. In one embodiment, the driver 120 can manually input requests and / or a driver profile via the human-machine interface (HMI) of the on-board computer system 230. In some other embodiments, the driver 120 can input requests and / or a driver profile via other devices.

[0078] For example, driver 120 may carry a user terminal 130. Driver 120 may request simulations and manage the in-vehicle computer system 230 and the simulations via the user terminal 130. Driver 120 can configure a driver profile on the user terminal 130 and load that driver profile into the in-vehicle computer system 230. The driver profile may include information about the target vehicle in the target profile list, along with other driver-specific information items. Driver 120 may also manage the connection between EV110 and the cloud server 140. For example, driver 120 may configure the EV110's in-vehicle computer system 230 to establish a connection to the cloud server 140 using a mobile application on the user terminal 130.

[0079] In some embodiments, after the driver 120 enters the EV 110, the onboard computer system 230 may recognize the driver 120 via the EV 110's camera and make simulation requests via the camera. In some other embodiments, the onboard computer system 230 may recognize the driver 120 via a user terminal 130 wirelessly connected to the onboard computer system 230. For example, the wireless connection is a Bluetooth connection. After recognizing the driver 120, the onboard computer system 230 retrieves the driver profile associated with the driver 120. The onboard computer system 230 may retrieve the driver profile from the onboard computer system 230's memory device, from the driver 120's wirelessly connected user terminal 130, or from a cloud server 140.

[0080] Furthermore, in S604, the on-board computer system 230 may acquire configuration parameters for simulating the behavior of a target vehicle on the EV. The configuration parameters of the target vehicle may be settings or other parameters that affect how the vehicle operates. In some embodiments, the configuration parameters include at least information about the target vehicle and settings for the target vehicle for the driver. For example, after the on-board computer system 230 receives a simulation request from the driver 120, the on-board computer system 230 can enter simulation mode and start various simulation processes. The on-board computer system 230 may then acquire configuration parameters for the simulation process. Specifically, the on-board computer system 230 may acquire driver-related information, as well as target behavior and target vehicle information. Additionally, or optionally, safety information related to the simulation process may be acquired locally or remotely by the on-board computer system 230 from the cloud server 140. For example, safety information may include EV health information, local traffic / safety rules and regulations, and ambient information from driver assistance systems.

[0081] The driver profile may be obtained for driver-related information, and the target profile may also be obtained for target behavior and target vehicle information. The target profile may indicate the target behavior and / or the target vehicle to be simulated. The target profile may include various types of information such as horsepower / torque curves, weight distribution, suspension constants / types / programming, steering ratio, wheelbase, vehicle type, fuel consumption curves, dashboard data, steering control weight, accelerator pedal feel, brake pedal feel, braking characteristic values, or combinations thereof. The target behavior is not initially configured (initialized) on the EV110.

[0082] In certain embodiments, the target profile may be included in the driver profile. Thus, the onboard computer system 230 may obtain the target vehicle from the driver profile of driver 120. In certain circumstances, obtaining the target profile of the target vehicle may involve using an onboard camera to obtain personal information of the EV driver and retrieving the driver profile and / or target profile associated with the personal information of the EV driver. In some embodiments, driver 120 may also input the target vehicle to the onboard computer system 230 via an input interface of the onboard computer system 230.

[0083] After optionally or additionally acquiring configuration parameters, the on-board computer system 230 determines, based on safety information, whether it is safe to start the simulation before starting it. For example, the on-board computer system 230 may assess the health of the EV based on engine fault codes, exceeded maintenance deadlines, and low tire pressure. After starting the simulation, the on-board computer system 230 may perform a safety check to determine whether it is safe to continue the simulation. Specifically, the on-board computer system 230 may perform a first safety check on the configuration parameters to determine whether the configuration parameters are within the safe range (first safety range) of the EV 110. If a particular configuration parameter is outside the safe range, the on-board computer system 230 may prompt an error message or terminate the simulation mode. If the first safety check is passed, the on-board computer system 230 may enter simulation mode and continue the simulation process.

[0084] Furthermore, in S606, the on-board computer system 230 may acquire multiple vehicle parameters of the EV110. These multiple vehicle parameters of the EV include at least the EV's runtime parameters and the EV's driving conditions. For example, the multiple vehicle parameters may include steering parameters, acceleration and deceleration parameters, and suspension parameters. Steering parameters may include steering wheel position, brake pedal position, shock position, vehicle weight distribution, torque vector, road surface condition, battery availability, or a combination thereof. Acceleration and deceleration parameters may include steering position, road surface condition, confirmed traction force, available power, motor temperature, battery pack temperature, gyro reading, accelerator reading, suspension position, throttle position, brake pedal position, regenerative settings, or a combination thereof. Some parameters may appear in two or more of the steering parameters, acceleration and deceleration parameters, and suspension parameters. The on-board computer system 230 may acquire multiple vehicle parameters of the EV110 in real time from various subsystems or components of the EV110. Some vehicle parameters are dynamically changing and can be acquired from the EV110's sensors. Some other vehicle parameters are static and can be retrieved from an EV database on a cloud server. Thus, the onboard computer system 230 may retrieve multiple vehicle parameters of the EV 110 locally and / or remotely from the cloud server.

[0085] Furthermore, in S608, the on-board computer system 230 may perform a target vehicle simulation process using a vehicle simulator model to obtain one or more control parameters for controlling the EV to realize the behavior, actions, and / or characteristics of the target vehicle on the EV, based on a plurality of configuration parameters and a plurality of vehicle parameters. The vehicle simulator model is a neural network trained to reflect the relationships between a plurality of vehicle parameters and a plurality of configuration parameters as inputs and one or more control parameters as outputs. More specifically, the plurality of configuration parameters and a plurality of vehicle parameters may be provided to the simulator as input parameters so that the simulator 402 can generate a plurality of output parameters that reflect the target behavior of the target vehicle. One or more control parameters may be output settings or other output parameters that control the operation of the EV. Examples of one or more control parameters include one or more of the following: target turning angle, target acceleration or deceleration, target drive wheels, target traction settings, target handling characteristics, and target engine sound.

[0086] In some embodiments, to conserve battery charging for the EV110, the on-board computer system 230 may offload the execution of the target vehicle simulation process to a cloud server 140. After completing the target vehicle simulation process, the cloud server 140 returns several output parameters to the on-board computer system 230. In this case, data exchange between the on-board computer system 230 and the cloud server 140 via wireless communication may cause a slight delay.

[0087] Furthermore, the on-board computer system 230 may obtain output parameters from the simulator 402 to realize the target behavior of the target vehicle. After obtaining the output parameters, the on-board computer system 230 may perform a second safety check on the parameters based on safety information to determine whether a particular parameter (control parameter) is within the safety range (second safety range) of the EV110. If any parameter is outside the safety range, the on-board computer system 230 may generate an error message and may stop the use of the out-of-range parameter in any further process or action.

[0088] Furthermore, the in-vehicle computer system 230 may perform one or more actions to achieve the target behavior based on output parameters. For example, the in-vehicle computer system 230 may generate control parameters for relevant subsystems or components of the EV110 to control the subsystems / components and achieve the simulated target behavior of the target vehicle. For example, one or more control parameters may include steering control, powertrain control, suspension control, dashboard display, engine sound, haptic control, driver's seat control, or a combination thereof. The simulated behavior of the target vehicle may include vehicle handling characteristics, gear shifts, dynamic engine sound and vibration to the driver's seat, a simulated dashboard of the target vehicle, and a combination thereof.

[0089] Certain actions, such as display and audio-related actions, may be performed statically by the in-vehicle computer system 230, while other specific actions, such as powertrain and driving-related actions, may be performed dynamically during the operation of the EV110. For example, the in-vehicle computer system 230 may render different dashboard displays on the EV as target dashboards for a target vehicle. In some embodiments, the in-vehicle computer system 230 may perform automatic dashboard adjustments on the EV110 as target dashboards for a target vehicle. For example, the in-vehicle computer system 230 may divide the electric dashboard of the EV110 into multiple zones, measure the ambient light luminance of each zone using one or more light sensors, and adjust the contrast, luminance, and content of each zone based on the ambient light luminance of each zone.

[0090] In one embodiment, based on output parameters, the on-board computer system 230 can adjust specific subsystems to simulate a target turning angle, target steering ratio, target weight distribution, and target wheelbase. In another embodiment, based on output parameters, the on-board computer system 230 can adjust specific subsystems to simulate a target acceleration or deceleration, target drive wheels, target traction settings, and target handling characteristics. In yet another embodiment, based on output parameters, the on-board computer system 230 can adjust the on-board speaker subsystem to simulate a target engine sound. In yet another embodiment, based on output parameters, the on-board computer system 230 can perform driver's seat modifications, including tightening bolts, changing stiffness, changing lumbar support, or a combination thereof, within a preset time, and then resume driver's seat modifications after the preset time has elapsed.

[0091] Furthermore, the on-board computer system 230 may perform one or more data operations based on the simulated target vehicle on the EV. That is, specific vehicle-related data can be processed and / or analyzed in various ways based on the virtual vehicle, i.e., the simulated target vehicle. For example, the on-board computer system 230 may acquire the location of the EV 110 and perform further location-based actions such as determining local driving restrictions corresponding to that location and applying the local driving restriction restrictions to the control parameters of the EV 110. In one embodiment, the on-board computer system 230 may collect data from the simulation process, as well as vehicle data of the simulated target vehicle, anonymize the collected data, and upload it to the cloud server 140 to train a vehicle simulator model. For example, the collected data may include usage statistics such as simulation period, location, and startup frequency, as well as error logs, such as when the simulator 402 fails to initialize or is stopped by the safety module 416 during operation. In another embodiment, the on-board computer system 230 may collect simulated trip data of the driver 120 and upload the trip data to a social media site identified by the driver 120. Other data manipulations may also be performed.

[0092] In some embodiments, the subject vehicle is a different vehicle from an EV, the EV is configured with adjustable seats, the behavior of the subject vehicle includes at least a seat profile, and the bolster lumbar support, recline angle, distance from the steering wheel, and seat depth of the EV's adjustable seat are adjusted to simulate those of the subject vehicle's seat.

[0093] In some embodiments, the adjustable seats of the EV are controlled to gradually return to their original settings by the EV driver after a predetermined period of time has elapsed.

[0094] In some embodiments, the vehicle in question is an ICE vehicle, and the EV is configured with a massage actuator in the driver's seat, and the behavior of the vehicle in question includes simulating the vibration of the ICE engine by vibrating the massage actuator in the driver's seat.

[0095] In some embodiments, the subject vehicle is a different vehicle from an EV, the EV is equipped with an olfactory fragrance dispenser, and the behavior of the subject vehicle includes a fragrance profile such that the olfactory fragrance dispenser is controlled to release a fragrance, such as the scent of real leather or vegan leather, to simulate the scent present inside the subject vehicle.

[0096] Figure 7 illustrates a specific application of the simulation system for an EV according to the embodiments of this disclosure. As shown in Figure 7, the target vehicle simulation system 400 is provided with various input parameters for simulating the target behavior of the target vehicle on the EV 110. Specifically, a target profile of the target vehicle 702, a number of vehicle parameters 704, a vehicle simulator model 706, a driver profile 708, and position information 710 are provided as inputs to the simulation system 400, and the simulation system 400 generates output parameters such as steering control 740, powertrain control 742, suspension control 744, dashboard display 746, engine sound 748, haptic control 750, and driver's seat control 752.

[0097] The target profile of the target vehicle 702 includes configuration parameters for simulating the behavior of the target vehicle on the EV110, and the target vehicle may include an ICE vehicle or an EV different from the EV110. Vehicle parameters 704 are acquired on the EV110 during operation and provided to the simulation system 400. The vehicle simulator model 706 may be an updated simulator model for the simulation system 400 and may be loaded into the on-board computer system 230 to replace the simulator model of the simulation system 400. That is, the on-board computer system 230 may perform version control or program updates by providing the vehicle simulator model 706 during the operation of the EV110. The driver profile 708 includes information about the driver of the EV110. Location information 710 may be taken from the GPS device of the EV110. Location information 710 can be used to enforce local government rules and regulations related to the real-time location of the EV110 or can be used as part of trip data. In some embodiments, the in-vehicle computer system 230 records trip data, anonymizes the recorded trip data, and makes the anonymized trip data available to the cloud server 140 for retrieval as training data for the vehicle simulator model 706. Meanwhile, the recorded trip data may be uploaded to social media specified in the driver profile 708.

[0098] Steering control 740 includes a target turning angle, target steering ratio, target weight distribution, target wheelbase, or a combination thereof. Powertrain control 742 may include a target acceleration, target deceleration, target drive wheels, target traction setting, target handling characteristics, or a combination thereof. Suspension control 744 includes a target suspension setting. Dashboard display 746 is a display device that simulates the dashboard of the target vehicle. Engine sound 748 dynamically simulates the engine sound of the target vehicle if the target vehicle is an internal combustion engine (ICE) vehicle. Tactile control 750 includes vibration of the steering wheel 228, vibration of the driver's seat 226, feel of the accelerator pedal 208, or a combination thereof. For example, the EV has a subwoofer under the driver's seat, which is controlled to simulate the vibration of an ICE engine. In another example, cabin speakers located at the rear of the EV are controlled to output exhaust sound. Cabin speakers located at the front of the EV are controlled to output turbo noise. In another example, the EV is equipped with a massage actuator in the driver's seat, which is controlled to simulate the vibrations of an ICE engine. The driver's seat control 752 includes a series of adjustments to the driver's seat when the EV 110 switches from normal mode to simulation mode. In some other embodiments, certain parameters and controls may be excluded, and additional parameters and controls may be included. This disclosure is not limited to these additions and / or omissions.

[0099] Accordingly, embodiments of the present disclosure provide an in-vehicle simulation method and system for an EV that simulates the behavior of a target vehicle on the EV. While driving the EV, the driver can request a simulation of the target vehicle's behavior and enjoy the look and feel of the target vehicle and the pleasure of driving it. The in-vehicle simulation system also allows the driver to share trip data collected while the EV is operating in simulation mode on social media. When the EV is operating in simulation mode, vehicle data generated by the in-vehicle simulation system is also collected and can be uploaded to a server as training data for training a new vehicle simulator model or for retraining and updating the current vehicle simulator model.

[0100] The embodiments described above illustrate in detail the objectives, technical solutions, and beneficial effects of this disclosure. The above disclosed embodiments are not all embodiments of the present invention, but only a selection of embodiments, and should not be used to limit the scope of the present invention. Any other embodiments derived based on the above embodiments, assuming no creative work by those skilled in the art, fall within the scope of the present invention. Furthermore, under non-consistent circumstances, embodiments and features in embodiments may be combined with each other. Accordingly, any changes, equivalent substitutions, and modifications made in accordance with this disclosure remain within the scope of this disclosure.

Claims

1. A simulation method for electric vehicles (EVs), Processing to receive a request from the driver of the electric vehicle to run a simulation of the target vehicle on the electric vehicle, A process for obtaining a plurality of configuration parameters for simulating the behavior of the target vehicle on the electric vehicle, including at least information about the target vehicle and settings for the target vehicle for the driver, A process for obtaining a plurality of vehicle parameters of the electric vehicle, including at least the runtime parameters of the electric vehicle and the driving conditions of the electric vehicle, A process of performing a simulation process using a vehicle simulator model to obtain one or more control parameters for controlling the electric vehicle to realize the behavior, actions, and / or characteristics of the target vehicle on the electric vehicle, based on the plurality of vehicle parameters and the plurality of configuration parameters, wherein the vehicle simulator model is a neural network trained to reflect the relationships between (i) the plurality of vehicle parameters and the plurality of configuration parameters and (ii) the one or more control parameters, A process for collecting vehicle data during the simulation, wherein the vehicle data includes the plurality of configuration parameters and the one or more control parameters. A process to anonymize the collected vehicle data and generate anonymized vehicle data, A method comprising uploading the anonymized vehicle data to a server in order to retrain and update the vehicle simulator model to improve the user experience, if permitted by the regulations and / or rules of the area in which the electric vehicle or the driver is located.

2. The method according to claim 1, wherein the subject vehicle is an internal combustion engine (ICE) vehicle, and the behavior of the subject vehicle includes at least the engine noise of the ICE vehicle.

3. The electric vehicle is equipped with a subwoofer and cabin speakers located under the driver's seat, and the method is as follows: The engine sound of the ICE vehicle is output through the cabin speaker of the electric vehicle, The method according to claim 2, further comprising controlling the subwoofer via one or more control parameters to simulate vibrations of the ICE engine.

4. Obtaining one or more control parameters for controlling the electric vehicle to realize the behavior, actions, and / or characteristics of the target vehicle on the electric vehicle is: The method according to claim 2, further comprising outputting exhaust noise through a cabin speaker located at the rear of the electric vehicle, and / or outputting turbo noise through a cabin speaker located at the front of the electric vehicle.

5. The method according to claim 1, wherein the subject vehicle is a different vehicle from the electric vehicle, the electric vehicle is configured to have adjustable seats, and the behavior of the subject vehicle is adjusted, at least by the seat profile, to simulate the bolster lumbar support, recline angle, distance from the steering wheel, and seat depth of the adjustable seats of the electric vehicle to those of the seats of the subject vehicle.

6. The method according to claim 5, wherein the adjustable seat of the electric vehicle is controlled to be returned to its original setting in stages by the driver of the electric vehicle after a predetermined period of time has elapsed.

7. The method according to claim 1, wherein the subject vehicle is an ICE vehicle, the electric vehicle is configured to have a massage actuator in the driver's seat, and the behavior of the subject vehicle includes controlling the massage actuator in the driver's seat to vibrate in a manner that simulates the vibration of an ICE engine.

8. The method according to claim 1, wherein the target vehicle is a different vehicle from the electric vehicle, the electric vehicle is equipped with an olfactory fragrance dispenser, and the behavior of the target vehicle is adjusted so that the olfactory fragrance dispenser releases a fragrance to simulate a fragrance present in the target vehicle, according to a fragrance profile.

9. A simulation method for electric vehicles (EVs), Processing to receive a request from the driver of the electric vehicle to run a simulation of the target vehicle on the electric vehicle, A process for obtaining a plurality of configuration parameters for simulating the behavior of the target vehicle on the electric vehicle, including at least information about the target vehicle and settings for the target vehicle for the driver, A process for obtaining a plurality of vehicle parameters of the electric vehicle, including at least the runtime parameters of the electric vehicle and the driving conditions of the electric vehicle, A process of performing a simulation process using a vehicle simulator model to obtain one or more control parameters for controlling the electric vehicle to realize the behavior, actions, and / or characteristics of the target vehicle on the electric vehicle, based on the plurality of vehicle parameters and the plurality of configuration parameters, wherein the vehicle simulator model is a neural network trained to reflect the relationships between (i) the plurality of vehicle parameters and the plurality of configuration parameters and (ii) the one or more control parameters, A process for obtaining safety information related to the aforementioned simulation, Before starting the simulation, a process to determine whether it is safe to start the simulation, and a process to execute the simulation in response to the determination that it is safe to start the simulation. A method comprising: performing a safety check after starting the simulation to determine whether it is safe to continue the simulation; and stopping the simulation in response to at least one of: (i) a determination that it is not safe to continue the simulation, or (ii) receiving a request from the driver to stop the simulation.

10. A simulation system for electric vehicles (EVs), Multiple input devices configured to provide multiple vehicle parameters, Memory containing program instructions, The system comprises the memory and a processor coupled to the plurality of input devices, and when the program instruction is executed, the processor The electric vehicle receives a request from the driver of the electric vehicle to perform a simulation of the target vehicle on the electric vehicle. Obtain a number of configuration parameters for simulating the behavior of the target vehicle on the electric vehicle, including at least information about the target vehicle and settings for the target vehicle for the driver. Obtain a plurality of vehicle parameters of the electric vehicle, including at least the runtime parameters of the electric vehicle and the driving conditions of the electric vehicle. The simulation process involves using a vehicle simulator model to obtain one or more control parameters for controlling the electric vehicle to realize the behavior, actions, and / or characteristics of the target vehicle on the electric vehicle, based on the plurality of vehicle parameters and the plurality of configuration parameters, wherein the vehicle simulator model is a neural network trained to reflect the relationships between (i) the plurality of vehicle parameters and the plurality of configuration parameters and (ii) the one or more control parameters, and the simulation process is performed. During the simulation, vehicle data including the multiple configuration parameters and one or more control parameters is collected. The collected vehicle data is anonymized to generate anonymized vehicle data. A system configured to upload the anonymized vehicle data to a server in order to retrain and update the vehicle simulator model to improve the user experience, if permitted by the regulations and / or rules of the area in which the electric vehicle or the driver is located.

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