Vehicle management systems and electric vehicles

Abstract

The vehicle management system is applicable to electric vehicles that use an electric motor as their power source. The system generates sound and outputs it through speakers mounted on the electric vehicle. It acquires driving status information indicating the driving state of the electric vehicle. Based on this driving status information, it determines the level of passive driving, indicating the degree of dangerous driving. The system then modifies the sound and / or changes the sound options based on the level of passive driving.

Description

Technical Field

[0001] This disclosure relates to electric vehicles in which an electric motor is used as a power source for driving. Background Technology

[0002] Patent Document 1 discloses a sound control device mounted on a vehicle capable of being driven by an electric motor. The sound control device displays the engine sound generated during gear shifting in a motor-driven vehicle in real time.

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent Application Publication No. 2011-215437 Summary of the Invention

[0006] The problem that the invention aims to solve

[0007] The aim is to suppress dangerous driving of vehicles. However, dangerous driving is not considered at all in Patent Document 1 mentioned above.

[0008] Methods for solving problems

[0009] The first point concerns a vehicle management system applied to electric vehicles that use electric motors as the power source for driving.

[0010] The vehicle management system has one or more processors.

[0011] One or more processors generate sound, which is then output through speakers mounted on an electric vehicle.

[0012] One or more processors acquire driving status information representing the driving status of the electric vehicle.

[0013] One or more processors obtain a degree of passive driving, representing the extent of dangerous driving in an electric vehicle, based on driving state information.

[0014] One or more processors may change the sound and / or change the sound options based on the level of passive driving.

[0015] The second viewpoint concerns electric vehicles that use electric motors as the power source for driving.

[0016] Electric vehicles have one or more processors.

[0017] One or more processors generate sound, which is then output through speakers mounted on an electric vehicle.

[0018] One or more processors acquire driving status information representing the driving status of the electric vehicle.

[0019] One or more processors obtain a degree of passive driving, representing the extent of dangerous driving in an electric vehicle, based on driving state information.

[0020] One or more processors may change the sound and / or change the sound options based on the level of passive driving.

[0021] The third perspective concerns vehicle management systems applied to electric vehicles that use electric motors as the power source for driving.

[0022] Electric vehicles have a simulation mode that simulates the driving characteristics of virtual vehicles.

[0023] The vehicle management system has one or more processors.

[0024] One or more processors acquire driving status information representing the driving status of the electric vehicle.

[0025] One or more processors obtain a degree of passive driving, representing the extent of dangerous driving in an electric vehicle, based on driving state information.

[0026] One or more processors can vary the options for virtual vehicles that can be used in simulation mode based on the degree of passive driving.

[0027] Invention Effects

[0028] According to the first and second viewpoints, sound is output through a speaker mounted on the electric vehicle. Furthermore, the sound changes and / or the sound options change according to the level of passive driving, which indicates the degree of dangerous driving by the electric vehicle. Through such changes in sound and / or sound options, the driver can become aware of dangerous driving. As a result, the driver can control and suppress dangerous driving.

[0029] According to the third perspective, electric vehicles possess a simulation mode that mimics the driving characteristics of a virtual vehicle. Furthermore, the available virtual vehicle options change in the simulation mode based on the level of negative driving, which indicates the degree of dangerous driving. Through these changes in virtual vehicle options, the driver can become aware of dangerous driving. As a result, the driver can control and suppress dangerous driving. Attached Figure Description

[0030] Figure 1 This is a conceptual diagram representing electric vehicles and vehicle management systems.

[0031] Figure 2 This is a block diagram illustrating an example of the basic functional structure of a vehicle management system.

[0032] Figure 3 This is a block diagram representing other examples of the basic functional structure of a vehicle management system.

[0033] Figure 4 This is a conceptual diagram used to illustrate an outline of sound management that takes dangerous driving into account.

[0034] Figure 5 This is a block diagram illustrating an example of the functional structure of a vehicle management system.

[0035] Figure 6 These are conceptual diagrams illustrating various examples of benchmarks used to illustrate the degree of passive driving.

[0036] Figure 7 This is a block diagram illustrating an example of the functional structure of the engine sound generation unit.

[0037] Figure 8 This is another block diagram illustrating the functional structure of a vehicle management system.

[0038] Figure 9 This is another example of a block diagram illustrating the functional structure of a vehicle management system.

[0039] Figure 10 This is a block diagram used to illustrate the vehicle-mounted device and the management server.

[0040] Figure 11 This is a block diagram used to illustrate the first example of how a vehicle management system is used.

[0041] Figure 12 This is a block diagram illustrating the second example of how a vehicle management system is used.

[0042] Figure 13 This is a block diagram used to illustrate the third example of how a vehicle management system is used.

[0043] Figure 14 This is the fourth example of a block diagram used to illustrate how a vehicle management system is used.

[0044] Figure 15 This is a block diagram representing a first structural example of the power control system of an electric vehicle.

[0045] Figure 16 This is a diagram showing examples of the engine model, clutch model, and transmission model that make up the MT vehicle model.

[0046] Figure 17 This is a graph showing the torque characteristics of the electric motor achieved through electric motor control using the MT vehicle model.

[0047] Figure 18 This is a block diagram representing a second structural example of the power control system for an electric vehicle.

[0048] Figure 19This is another example of a block diagram illustrating the functional structure of a vehicle management system. Detailed Implementation

[0049] The embodiments of this disclosure will be described with reference to the accompanying drawings.

[0050] 1. Electric vehicles and vehicle management systems

[0051] Figure 1 This is a conceptual diagram illustrating the electric vehicle 10 and the vehicle management system 100 according to this embodiment. The electric vehicle 10 includes an electric motor 44. Examples of electric motors 44 include a brushless DC motor and a three-phase AC synchronous motor. The electric vehicle 10 uses the electric motor 44 as a power unit for driving.

[0052] In addition, the electric vehicle 10 is equipped with various sensors 11. These sensors 11 detect the driving status of the electric vehicle 10. Examples of these sensors 11 include accelerator position sensors, brake position sensors, steering angle sensors, steering torque sensors, wheel speed sensors, acceleration sensors, speed sensors, position sensors, and recognition sensors. The accelerator position sensor detects the amount of accelerator pedal operation. The brake position sensor detects the amount of brake pedal operation. The steering angle sensor detects the steering angle of the steering wheel. The steering torque sensor detects the steering torque of the steering wheel. The wheel speed sensors detect the rotational speed of the wheels of the electric vehicle 10. The acceleration sensors detect the lateral acceleration and longitudinal acceleration of the electric vehicle 10. The rotational speed sensor detects the rotational speed of the electric motor 44. The position sensors detect the position of the electric vehicle 10. Examples of position sensors include Global Navigation Satellite System (GNSS) sensors. Recognition sensors are used to identify (detect) the surrounding conditions of the electric vehicle 10. Examples of recognition sensors include cameras, LiDAR (Light Detection and Range), and radar.

[0053] Furthermore, the electric vehicle 10 is equipped with one or more speakers 70. For example, the speaker 70 is an interior speaker that outputs sound into the interior of the electric vehicle 10. As another example, the speaker 70 may also be an exterior speaker that outputs sound into the exterior of the electric vehicle 10. The electric vehicle 10 may also have both interior and exterior speakers.

[0054] The vehicle management system 100 is applied to and manages the electric vehicle 10. The entire vehicle management system 100 can also be integrated into the electric vehicle 10. As another example, at least a portion of the vehicle management system 100 can be contained in a management server external to the electric vehicle 10. In this case, the vehicle management system 100 can also remotely manage the electric vehicle 10. As yet another example, the vehicle management system 100 can also be distributed across the electric vehicle 10 and the management server.

[0055] Generally, a vehicle management system 100 includes one or more processors 101 (hereinafter referred to as processor 101) and one or more storage devices 102 (hereinafter referred to as storage device 102). The processor 101 performs various processes. Examples of processors 101 include general-purpose processors, dedicated processors, central processing units (CPUs), graphics processing units (GPUs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), integrated circuits, conventional circuits, and / or combinations thereof. The processor 101 may also be referred to as a circuitry or processing circuitry. A circuitry is hardware programmed to implement or perform functions. The storage device 102 stores (saves) various information. Examples of storage devices 102 include volatile memory, non-volatile memory, HDDs (Hard Disk Drives), SSDs (Solid State Drives), etc. The functions of the vehicle management system 100 are realized through the cooperation of the processor 101 and the storage device 102.

[0056] One or more vehicle management programs 105 (hereinafter referred to as vehicle management programs 105) are computer programs executed by processor 101. The functions of the vehicle management system 100 can also be implemented through the cooperation of processor 101 executing vehicle management programs 105 and storage device 102. Vehicle management programs 105 are stored in storage device 102. Alternatively, vehicle management programs 105 can also be recorded on a computer-readable recording medium.

[0057] For example, the vehicle management system 100 has the function of a sound management system for managing sounds related to the electric vehicle 10. In particular, the vehicle management system 100 generates and manages the sound output from the speaker 70 mounted on the electric vehicle 10. Furthermore, the vehicle management system 100 outputs the generated sound through the speaker 70 mounted on the electric vehicle 10.

[0058] For example, the vehicle management system 100 generates a "simulated engine sound" that mimics the engine sound of a motorized vehicle. Furthermore, the vehicle management system 100 outputs the simulated engine sound through a speaker 70 mounted on the electric vehicle 10. Additionally, a motorized vehicle refers to a vehicle equipped with an engine (internal combustion engine) and using the engine as a power unit for propulsion.

[0059] The sound output from speaker 70 is not limited to simulated engine sounds. For example, the sound could also be simulated driving sounds that mimic the driving sounds of a moving body other than a car (e.g., a tram, an airplane, etc.). As another example, the sound could be navigation voice. As yet another example, the sound could be music.

[0060] In the following description, as an example, "analog engine sound" is considered as the sound output from speaker 70. However, this disclosure can also be applied to other sounds. In general, "analog engine sound" and "engine sound" in the following description will be replaced with "sound".

[0061] Figure 2 This is a block diagram illustrating an example of the basic functional structure of a vehicle management system 100. The vehicle management system 100 includes a driving status acquisition unit 110, an audio source data management unit 120, an engine sound generation unit 130, and an output unit 140 as functional blocks. These functional blocks can also be implemented, for example, through the cooperation of a processor 101 executing a vehicle management program 105 and a storage device 102.

[0062] The driving state acquisition unit 110 acquires driving state information (DRV) indicating the driving state of the electric vehicle 10. The driving state information DRV includes information related to the driver's driving operations, information related to the driving state of the electric vehicle 10, and information related to the surrounding conditions of the electric vehicle 10. Typically, the driving state information DRV includes information detected by sensors 11 mounted on the electric vehicle 10. For example, the driving state information DRV includes the amount of accelerator pedal operation (accelerator opening), the amount of brake pedal operation (brake opening), steering angle, steering speed, steering torque, wheel speed, vehicle speed, front-rear acceleration, lateral acceleration, and the rotational speed of the electric motor 44. The driving state information DRV may also include the position of the electric vehicle 10. The driving state information DRV may also include the surrounding conditions of the electric vehicle 10 identified (detected) by identification sensors.

[0063] Furthermore, the operating status information DRV includes the virtual engine speed Ne. Here, it is assumed that the electric vehicle 10 uses a virtual engine as its driving power unit. The virtual engine speed Ne is assumed to be the speed of the virtual engine when the electric vehicle 10 is driven by the virtual engine. For example, the operating status acquisition unit 110 can also calculate the virtual engine speed Ne in a manner that increases with the wheel speed. In addition, when the electric vehicle 10 has a manual mode (MT mode) as described later, the driving status acquisition unit 110 can also calculate the virtual engine speed Ne in manual mode based on the wheel speed, the combined reduction ratio, and the slip ratio of the virtual clutch. Details of the calculation method for the virtual engine speed Ne in manual mode will be described later.

[0064] The sound source data management unit 120 stores and manages the basic sound source data 200 used to generate simulated engine sounds. The sound source data management unit 120 is primarily implemented by one or more storage devices 102. Typically, the basic sound source data 200 includes various types of sound source data. These various types of sound source data include, for example, sound source data for sounds caused by engine combustion (for low speed, medium speed, and high speed), sound source data for sounds caused by drive systems such as gears (for low speed, medium speed, and high speed), noise sound source data, and sound source data for event sounds (e.g., creaking sounds, engine stop sounds), etc. Each sound source data is pre-generated through simulations based on engine models and vehicle models of an engine vehicle. Each sound source data can be flexibly adjusted; that is, at least one of the sound pressure level and frequency of the sound represented by the sound source data can be flexibly adjusted.

[0065] The engine sound generation unit 130 (engine sound simulator) is a simulator that generates simulated engine sounds. The engine sound generation unit 130 obtains at least a portion of the operating state information DRV from the operating state acquisition unit 110. Specifically, the engine sound generation unit 130 obtains information about the virtual engine speed Ne and vehicle speed from the operating state acquisition unit 110. Additionally, the engine sound generation unit 130 reads basic sound source data 200 from the sound source data management unit 120. Furthermore, the engine sound generation unit 130 generates simulated engine sounds corresponding to the operating state (virtual engine speed Ne, vehicle speed) of the electric vehicle 10 by combining one or more sound source data included in the basic sound source data 200. Engine sound data ES is data representing the generated simulated engine sound.

[0066] Furthermore, the generation of simulated engine sounds is a well-known technique and is not particularly limited in this embodiment. For example, simulated engine sounds can also be generated using well-known engine sound simulators used in games, etc. Alternatively, a method can be employed that includes a virtual engine speed Ne-frequency mapping and a virtual engine torque-sound pressure mapping, where the frequency of the simulated engine sound is increased or decreased proportionally to the virtual engine speed Ne, and the sound pressure is increased or decreased proportionally to the virtual engine torque.

[0067] The output unit 140 receives engine sound data ES generated by the engine sound generation unit 130. Furthermore, based on the engine sound data ES, the output unit 140 outputs analog engine sound through the speaker 70.

[0068] Figure 3 This is a block diagram illustrating other examples of the basic functional structure of a vehicle management system 100. Figure 3 In the example shown, the audio source data management unit 120 stores and manages various basic audio source data 200 (200-A, 200-B, 200-C, etc.) corresponding to multiple vehicle models (A, B, C, etc.). That is, the audio source data management unit 120 stores and manages the basic audio source data 200 for each vehicle model. Each basic audio source data 200 is pre-generated based on the engine model and vehicle model of the corresponding vehicle model. The driver can also specify their preferred vehicle model from among the multiple models. In this case, the engine sound generation unit 130 retrieves the basic audio source data 200 corresponding to the vehicle model specified by the driver. Then, the engine sound generation unit 130 uses the retrieved basic audio source data 200 (e.g., basic audio source data 200-B corresponding to vehicle model B) to generate a simulated engine sound. Thus, the driver can experience the feeling of driving their preferred vehicle model.

[0069] If Figure 3 The example shown can be generalized to suggest that there are multiple options for the sounds being simulated. For instance, multiple options could include simulated engine sounds for different car models. As other examples, multiple options could also include simulated drive sounds for various virtual moving objects (e.g., vehicles, trams, airplanes). In short, the driver can choose their preferred sound from multiple options.

[0070] 2. Sound management for dangerous driving has been taken into consideration.

[0071] 2-1. Overview

[0072] From a safety and traffic flow perspective, dangerous driving is not preferred. Therefore, this embodiment proposes a technology that can suppress dangerous driving.

[0073] Figure 4This is a conceptual diagram illustrating an outline of sound management that takes dangerous driving into consideration. According to this embodiment, a "Negative Driving Level NEG" is used to represent the degree of dangerous driving by the electric vehicle 10. The vehicle management system 100 can obtain the negative driving level NEG based on the aforementioned driving state information DRV. Specific examples of obtaining the negative driving level NEG will be described later.

[0074] Furthermore, the vehicle management system 100 changes the simulated engine sound output from the speaker 70 according to the level of passive driving (NEG). For example, the vehicle management system 100 reduces the audibility of the simulated engine sound as the level of passive driving (NEG) increases. As another example, the vehicle management system 100 may increase the noise component in the simulated engine sound as the level of passive driving (NEG) increases. As yet another example, the vehicle management system 100 may increase the unwanted sound component in the simulated engine sound as the level of passive driving (NEG) increases. As yet another example, the vehicle management system 100 may increase the "roaring" sound of the simulated engine sound as the level of passive driving (NEG) increases. As yet another example, the vehicle management system 100 may decrease the sound quality of the simulated engine sound as the level of passive driving (NEG) increases. When changing the simulated engine sound according to the level of passive driving (NEG), the simulated engine sound may also be changed from a default sound. Here, the default sound is the normal sound without considering the level of passive driving (NEG). As another example, the vehicle management system 100 can also mute the simulated engine sound or increase the sound pressure of the simulated engine sound when the passive driving level NEG exceeds the threshold.

[0075] As another example, the vehicle management system 100 can also change the option of simulating engine sound based on the level of passive driving (NEG) (see [reference]). Figure 3 For example, the vehicle management system 100 reduces the option to simulate engine sound as the level of negative driving (NEG) increases. While the option to simulate engine sound changes based on the level of negative driving (NEG), the option to simulate engine sound can also be changed from the default option. Here, the default option is the normal option when the level of negative driving (NEG) is not considered.

[0076] As another example, the vehicle management system 100 can also change the simulated engine sound based on the degree of passive driving (NEG), and change the options for the simulated engine sound.

[0077] Thus, according to this embodiment, the simulated engine sound changes and / or the option for simulating the engine sound changes based on the degree of passive driving (NEG), which indicates the degree of dangerous driving. Through such changes in the simulated engine sound and / or the option for simulating the engine sound, the driver can become aware that dangerous driving has been performed. As a result, the driver controls and suppresses dangerous driving. Suppression of dangerous driving is also preferable for safety and traffic flow.

[0078] As the level of passive driving (NEG) increases, the audibility of the simulated engine sound can decrease. The noise or unwanted sound components in the simulated engine sound can also increase. Alternatively, the "roaring" sound of the simulated engine sound can increase with higher NEG levels. The tone quality of the simulated engine sound can also decrease. When the NEG level exceeds a threshold, the simulated engine sound can be silenced as a penalty for the driver. This becomes a strong incentive for drivers who want to enjoy the simulated engine sound to avoid dangerous driving. As a result, dangerous driving is further suppressed.

[0079] As the level of passive driving (NEG) increases, the option to simulate engine sounds can be reduced. This provides a strong incentive for drivers who want to enjoy simulated engine sounds to avoid dangerous driving. As a result, dangerous driving is further suppressed.

[0080] The following provides a detailed explanation of the Negative Driving Level (NEG) and specific examples of its sound management.

[0081] 2-2. Specific examples of the degree of passive driving

[0082] Figure 5 This is a block diagram illustrating an example of the functional structure of the vehicle management system 100 according to this embodiment. Besides... Figure 2 In addition to the functional blocks shown, the vehicle management system 100 also includes a passive driving level acquisition unit 150. These functional blocks can also be implemented through the cooperation of the processor 101 executing the vehicle management program 105 and the storage device 102.

[0083] As described above, the driving state acquisition unit 110 acquires driving state information (DRV) indicating the driving state of the electric vehicle 10. The driving state information (DRV) includes information related to the driver's driving operations, information related to the driving state of the electric vehicle 10, and information related to the surrounding conditions of the electric vehicle 10. The negative driving level acquisition unit 150 receives the driving state information (DRV) from the driving state acquisition unit 110. Furthermore, based on the driving state information (DRV), the negative driving level acquisition unit 150 acquires a negative driving level (NEG) indicating the degree of dangerous driving by the electric vehicle 10.

[0084] Figure 6 These are conceptual diagrams illustrating various examples of the benchmark used to explain the Negative Driving Level (NEG) standard. The Negative Driving Level (NEG) is based on... Figure 6 It is obtained by at least one of the benchmarks shown.

[0085] 2-2-1. Relationship with speed limit

[0086] Exceeding the speed limit constitutes dangerous driving. Therefore, the negative driving level acquisition unit 150 can also acquire the negative driving level NEG based on whether or not the speed limit has been exceeded.

[0087] The speed limit of the road on which the electric vehicle 10 is traveling is obtained, for example, from the speed limit sign S set on that road. The speed limit sign S is identified using a camera mounted on the electric vehicle 10. The driving state acquisition unit 110 identifies the speed limit sign S by analyzing the image captured by the camera. Furthermore, the driving state acquisition unit 110 identifies the number recorded on the speed limit sign S based on the identified image of the speed limit sign S. That is, the driving state acquisition unit 110 acquires information about the speed limit indicated by the speed limit sign S. Typically, the driving state acquisition unit 110 identifies the speed limit sign S and the speed limit from the image using image recognition AI (Artificial Intelligence). The image recognition AI is pre-generated using learning methods such as deep learning.

[0088] As another example, if speed limit information is registered in the map information, the driving status acquisition unit 110 can also obtain the speed limit information based on the current position of the electric vehicle 10 and the map information. The current position of the electric vehicle 10 is obtained by a position sensor. The map information is pre-stored in the storage device 102.

[0089] Alternatively, the driving state acquisition unit 110 acquires the speed of the electric vehicle 10 from the wheel speed sensors. Or, the driving state acquisition unit 110 may calculate the speed based on the position change of the electric vehicle 10.

[0090] The driving status acquisition unit 110 determines whether the speed limit has been exceeded based on the speed of the electric vehicle 10 and the speed limit. In this case, the operating status information DRV includes whether the speed limit has been exceeded.

[0091] The passive driving level acquisition unit 150 acquires (calculates) the passive driving level NEG based on whether or not the speed limit is exceeded. More specifically, passive time is the time during which the speed exceeds the speed limit, i.e., the time during which the speed exceeds the speed limit. Total passive time is the sum of passive times. Passive ratio is the proportion of passive time relative to a certain period. In addition, passive frequency is the frequency at which the speed limit is exceeded within a certain period. Passive parameter is the total passive time, passive ratio, passive frequency, or a combination of two or more of them. The passive driving level acquisition unit 150 increases the passive driving level NEG as the passive parameter increases. Here, the passive driving level NEG can increase continuously or in stages. The relationship between the passive parameter and the passive driving level NEG can also be given by mapping.

[0092] 2-2-2. Acceleration and deceleration

[0093] Rapid acceleration implies dangerous driving. Therefore, the negative driving level acquisition unit 150 can also acquire the negative driving level NEG based on the acceleration of the electric vehicle 10.

[0094] The driving status acquisition unit 110 acquires the acceleration of the electric vehicle 10 from the acceleration sensor. The driving status information (DRV) includes the acceleration of the electric vehicle 10.

[0095] The passive driving level acquisition unit 150 acquires (calculates) the passive driving level NEG based on acceleration. More specifically, passive time is the time during which acceleration is above a threshold. Total passive time is the sum of passive times. Passive ratio is the proportion of passive time relative to a certain period. Additionally, passive frequency is the frequency at which acceleration is above a threshold within a certain period. Passive parameters are total passive time, passive ratio, passive frequency, or a combination of two or more of them. The passive driving level acquisition unit 150 increases the passive driving level NEG as the passive parameters increase. Here, the passive driving level NEG can increase continuously or in stages. The relationship between the passive parameters and the passive driving level NEG can also be given by mapping.

[0096] Sudden deceleration also implies dangerous driving. Therefore, the negative driving level acquisition unit 150 can also acquire the negative driving level NEG based on the deceleration of the electric vehicle 10. The method for acquiring the negative driving level NEG in this case is the same as in the case of acceleration described above, except that "acceleration" in the above description is replaced with "deceleration (absolute value)".

[0097] 2-2-3. Steering speed

[0098] Making a sharp turn implies dangerous driving. Therefore, the negative driving level acquisition unit 150 can also acquire the negative driving level NEG based on the steering speed of the steering wheel of the electric vehicle 10.

[0099] The driving status acquisition unit 110 calculates the steering speed based on the steering angle detected by the steering angle sensor. The driving status information (DRV) includes the steering speed.

[0100] The passive driving level acquisition unit 150 acquires (calculates) the passive driving level NEG based on steering speed. More specifically, passive time is the time during which the steering speed is above a threshold. Total passive time is the sum of passive times. Passive ratio is the proportion of passive time relative to a certain period. Additionally, passive frequency is the frequency at which the steering speed is above the threshold within a certain period. Passive parameters are total passive time, passive ratio, passive frequency, or a combination of two or more of them. The passive driving level acquisition unit 150 increases the passive driving level NEG as the passive parameters increase. Here, the passive driving level NEG can increase continuously or in stages. The relationship between the passive parameters and the passive driving level NEG can also be given by mapping.

[0101] 2-2-4. Workshop distance, TTC

[0102] Insufficient distance from the preceding vehicle implies dangerous driving. Therefore, the negative driving level acquisition unit 150 can also acquire the negative driving level NEG based on the distance from the preceding vehicle.

[0103] The driving status acquisition unit 110 uses identification sensors to acquire surrounding condition information representing the conditions around the electric vehicle 10. Examples of identification sensors include cameras, lidar, and radar. For example, the surrounding condition information includes images captured by a camera. As another example, the surrounding condition information may also include point group information obtained by lidar. The surrounding condition information also includes object information related to objects around the electric vehicle 10. Examples of objects around the electric vehicle 10 include pedestrians, bicycles, other vehicles (e.g., vehicles ahead, following, parallel, and parked), roadside structures (e.g., curbs, guardrails, and walls), white lines, signs, and signals. The object information represents the relative position and relative speed of the object relative to the electric vehicle 10. For example, by analyzing images obtained by a camera, objects can be identified and their relative positions calculated. Alternatively, objects can be identified and their relative positions and speeds obtained based on point group information obtained by lidar. The driving status information (DRV) includes object information. The relative distance to the vehicle ahead is equivalent to the inter-vehicle distance.

[0104] The passive driving level acquisition unit 150 acquires (calculates) the passive driving level NEG based on the inter-vehicle distance to the preceding vehicle. More specifically, the passive driving time is the time during which the inter-vehicle distance is less than a threshold. This threshold can be a function of the speed of the electric vehicle 10. That is, the threshold can also increase as the speed increases. The total passive driving time is the sum of the passive driving times. The passive driving ratio is the proportion of the passive driving time relative to a certain period. In addition, the passive driving frequency is the frequency at which the inter-vehicle distance is less than the threshold within a certain period. The passive driving parameter is the total passive driving time, the passive driving ratio, the passive driving frequency, or a combination of two or more of them. The passive driving level acquisition unit 150 increases the passive driving level NEG as the passive driving parameter increases. Here, the passive driving level NEG can increase continuously or in stages. The relationship between the passive driving parameter and the passive driving level NEG can also be given by a mapping.

[0105] Insufficient TTC (Time-To-Collision) relative to the preceding vehicle also implies dangerous driving. TTC is calculated based on the inter-vehicle distance and the speed of the electric vehicle 10. The passive driving level acquisition unit 150 can also acquire the passive driving level NEG based on the TTC. The method for acquiring the passive driving level NEG in this case is the same as in the case of inter-vehicle distance described above, except that "inter-vehicle distance" in the above description is replaced with "TTC". The threshold can also be a predetermined threshold that is independent of speed.

[0106] 2-2-5. Distance from surrounding objects

[0107] Insufficient distance (margin) from surrounding objects of the electric vehicle 10 implies dangerous driving. Examples of surrounding objects include pedestrians, bicycles, parallel vehicles, parked vehicles, roadside structures (e.g., curbs, guardrails, walls), etc. Therefore, the negative driving level acquisition unit 150 can also acquire the negative driving level NEG based on the distance from surrounding objects.

[0108] As described above, the Driving Status Information (DRV) includes object information related to surrounding objects around the electric vehicle 10. This object information includes the distance to the surrounding objects.

[0109] The passive driving level acquisition unit 150 acquires (calculates) the passive driving level NEG based on the distance to surrounding objects. More specifically, the passive driving time is the time during which the distance to surrounding objects is less than a threshold. This threshold can be a function of the speed of the electric vehicle 10. That is, the threshold can also increase as the speed increases. The total passive driving time is the sum of the passive driving times. The passive driving ratio is the proportion of the passive driving time relative to a certain period. In addition, the passive driving frequency is the frequency at which the distance to surrounding objects is less than the threshold within a certain period. The passive driving parameter is the total passive driving time, the passive driving ratio, the passive driving frequency, or a combination of two or more of them. The passive driving level acquisition unit 150 increases the passive driving level NEG as the passive driving parameter increases. Here, the passive driving level NEG can increase continuously or in stages. The relationship between the passive driving parameter and the passive driving level NEG can also be given by a mapping.

[0110] 2-2-6. Lane Changing Status

[0111] Frequent lane changes indicate dangerous driving. Furthermore, changing lanes in prohibited lane-changing areas also constitutes dangerous driving. Therefore, the passive driving level acquisition unit 150 can also acquire the passive driving level NEG based on the lane-changing status.

[0112] The driving status acquisition unit 110 detects the driver's active steering operation based on the detection results from the steering angle sensor and / or steering torque sensor. Additionally, the driving status acquisition unit 110 identifies the white lines surrounding the electric vehicle 10 and their types based on images captured by a camera. The driving status acquisition unit 110 can identify lane changes based on the detection results of the driver's steering operation and the identification results of the white lines. In the event of a lane change, the driving status acquisition unit 110 can determine whether the lane change was performed within a lane-changing prohibited area based on the type of white line.

[0113] As another example, when lane information is registered in the map information, the driving status acquisition unit 110 can identify the occurrence of a lane change based on the location of the electric vehicle 10 and the map information. When lane change permitted areas and lane change prohibited areas are registered in the map information, the driving status acquisition unit 110 can determine whether the lane change was performed in a lane change prohibited area.

[0114] Driving status information (DRV) includes lane change status. Lane change status can also include the frequency of lane changes within a certain period. Lane change status can also include whether a lane change was made in a prohibited lane-changing area.

[0115] The passive driving level acquisition unit 150 acquires (calculates) the passive driving level NEG based on the lane change status. For example, the higher the frequency of lane changes, the more the passive driving level acquisition unit 150 increases the passive driving level NEG. Here, the passive driving level NEG can increase continuously or in stages. The relationship between the frequency of lane changes and the passive driving level NEG can also be provided through mapping.

[0116] As another example, the passive driving level acquisition unit 150 can also increase the passive driving level NEG when a lane change is made in a lane change prohibited area. Conversely, the passive driving level acquisition unit 150 can also decrease the passive driving level NEG when a lane change is made in a lane change permitted area.

[0117] 2-2-7. Combination

[0118] It can also be a combination of two or more of the sub-segments 2-2-1 to 2-2-6 mentioned above. That is, the passive driving level acquisition unit 150 can also merge multiple passive driving level NEGs obtained based on multiple benchmarks to obtain the final passive driving level NEG.

[0119] 2-3. Sound management corresponding to the degree of passive driving

[0120] exist Figure 5 In the example shown, the passive driving level acquisition unit 150 outputs the passive driving level NEG to the engine sound generation unit 130. The engine sound generation unit 130 changes the generated simulated engine sound according to the passive driving level NEG.

[0121] For example, as the level of passive driving (NEG) increases, the engine sound generation unit 130 reduces the audibility of the simulated engine sound. For example, as the level of passive driving (NEG) increases, the engine sound generation unit 130 reduces audibility by increasing the noise component included in the simulated engine sound. As another example, the engine sound generation unit 130 may also reduce audibility by increasing unpleasant sounds (creaking, gurgling) included in the simulated engine sound as the level of passive driving (NEG) increases. As yet another example, the engine sound generation unit 130 may also reduce audibility by increasing unwanted sound components (sounds unrelated to the engine sound) included in the simulated engine sound as the level of passive driving (NEG) increases. The sound source data for noise, unpleasant sounds, and unwanted sounds are included in the basic sound source data 200.

[0122] As another example, the engine sound generation unit 130 can also reduce listenability by increasing the "roar" of the simulated engine sound as the negative driving level NEG increases. A DSP (Digital Signal Processor) can also be used to adjust the "roar" of the simulated engine sound. As another example, the engine sound generation unit 130 can also reduce listenability by decreasing the sound pressure level of the simulated engine sound as the negative driving level NEG increases. As another example, the engine sound generation unit 130 can also reduce listenability by decreasing the sound quality of the simulated engine sound as the negative driving level NEG increases. Sound quality is determined by frequency characteristics, distortion rate, SN ratio, dynamic range, etc.

[0123] Generally, the engine sound generation unit 130 changes at least one of the following aspects of the simulated engine sound: timbre, tone quality, sound pressure level, and frequency range, based on the degree of passive driving (NEG). DSP can also be used for adjusting timbre, tone quality, sound pressure level, and frequency range.

[0124] As another example, when the level of passive driving (NEG) exceeds a prescribed threshold, the engine sound generation unit 130 can also mute the simulated engine sound. That is, the engine sound generation unit 130 can also stop generating and outputting the simulated engine sound. This becomes a penalty for drivers who enjoy the simulated engine sound. Therefore, it also becomes a reward for suppressing dangerous driving.

[0125] As another example, the engine sound generation unit 130 can also suddenly increase the sound pressure of the simulated engine sound when the level of passive driving NEG exceeds a prescribed threshold. As a result, the driver is more likely to notice dangerous driving.

[0126] Figure 7 This is a block diagram illustrating an example of the functional configuration of the engine sound generation unit 130. Figure 7 In the example shown, the engine sound generation unit 130 includes a default sound generation unit 131 and a correction unit 132. The default sound generation unit 131 generates a default simulated engine sound ES0 based on driving state information DRV and basic sound source data 200. The default simulated engine sound ES0 is the typical simulated engine sound without considering the negative driving level NEG. The correction unit 132 receives the default simulated engine sound ES0 and the negative driving level NEG. Furthermore, the correction unit 132 corrects the default simulated engine sound ES0 according to the negative driving level NEG, thereby generating a simulated engine sound that reflects the negative driving level NEG. For example, as the negative driving level NEG increases, the correction unit 132 generates a simulated engine sound by reducing the audibility of the default simulated engine sound ES0. The correction unit 132 may also include a DSP.

[0127] like Figure 5 As shown, the vehicle management system 100 may include a user interface 160. The user interface 160 includes input devices and output devices. Examples of input devices include touch panels, buttons, switches, keyboards, microphones, etc. Examples of output devices include touch panels, displays, speakers, etc. When the current driving state is considered dangerous driving, the vehicle management system 100 may also notify the user (driver) of the dangerous driving situation via the user interface 160. For example, if the level of passive driving (NEG) is above a threshold, the vehicle management system 100 may also notify the user (driver) of the dangerous driving situation via the user interface 160. For example, the vehicle management system 100 may display visual information indicating the dangerous driving situation on a display device. As another example, the vehicle management system 100 may also output audible information indicating the dangerous driving situation from a speaker.

[0128] Figure 8 This is another block diagram illustrating the functional structure of a vehicle management system 100. (Appropriate omissions are allowed.) Figure 5 The example shown is a repetitive illustration. In Figure 8 In the example shown, the passive driving level acquisition unit 150 outputs the passive driving level NEG to the audio source data management unit 120. The audio source data management unit 120 changes the types of available basic audio source data 200 based on the passive driving level NEG. The available basic audio source data 200 is provided, for example, from a management server. The change in the types of available basic audio source data 200 is equivalent to the change in the available simulated engine sounds options.

[0129] For example, as the level of passive driving (NEG) increases, the audio source data management unit 120 reduces the types of available basic audio source data 200. In other words, as the level of passive driving (NEG) increases, the audio source data management unit 120 reduces the options for simulated engine sounds. While the option for simulated engine sound can be changed based on the level of passive driving (NEG), it can also be changed from the default option. Here, the default option is the normal option when the level of passive driving (NEG) is not considered.

[0130] The user (driver) of the electric vehicle 10 can specify a desired sound source from multiple types of basic sound source data 200 via the user interface 160. The engine sound generation unit 130 generates a simulated engine sound using the basic sound source data 200 specified by the user. That is, the user of the electric vehicle 10 can specify a desired simulated engine sound from the options via the user interface 160.

[0131] Figure 9 This is another example of a block diagram illustrating the functional structure of a vehicle management system 100. Figure 9 The example shown is Figure 5 and Figure 8 The combination of these factors means that, depending on the level of passive driving (NEG), the simulated engine sound changes, and the options for simulating the engine sound also change.

[0132] Furthermore, as stated above, the sounds described in this disclosure are not limited to simulated engine sounds. This disclosure can also be applied to other sounds different from simulated engine sounds.

[0133] 2-4. Effects

[0134] As explained above, according to this embodiment, sound is output through a speaker 70 mounted on the electric vehicle 10. Furthermore, the sound changes and / or the sound options change according to the degree of dangerous driving (NEG), which indicates the degree of dangerous driving by the electric vehicle 10. Through such changes in sound and / or sound options, the driver can become aware that dangerous driving has occurred. As a result, the driver controls and suppresses dangerous driving. Suppression of dangerous driving is also preferable for safety and traffic flow.

[0135] As the level of passive driving (NEG) increases, the audibility of the sound can decrease. The amount of noise or unwanted sound components in the sound can also increase. The "rumbling" sound can also increase. The sound quality can also decrease. When the NEG level exceeds a threshold, the sound can become silent. These factors create a strong incentive for drivers who want to enjoy the sound to avoid dangerous driving. As a result, dangerous driving is further suppressed.

[0136] As the level of passive driving (NEG) increases, the number of sound options also decreases. This becomes a strong incentive for drivers who want to enjoy the sounds to avoid dangerous driving. As a result, dangerous driving is further suppressed.

[0137] 3. Various application methods

[0138] The following describes various ways of using the vehicle management system 100 of this embodiment.

[0139] Figure 10 This is a block diagram illustrating the on-board device 400 and the management server 300 that constitute the vehicle management system 100. The on-board device 400 and the management server 300 can communicate via a communication network.

[0140] The vehicle-mounted device 400 is mounted on an electric vehicle 10. The vehicle-mounted device 400 includes one or more processors 401 (hereinafter simply referred to as processor 401), one or more storage devices 402 (hereinafter simply referred to as storage devices 402), and a communication device 403. The processor 401 performs various processes. Examples of processors 401 include general-purpose processors, special-purpose processors, CPUs, GPUs, ASICs, FPGAs, integrated circuits, conventional circuits, and / or combinations thereof. The processor 401 may also be referred to as a circuitry or processing circuitry. The storage device 402 stores (saves) various information. Examples of storage devices 402 include volatile memory, non-volatile memory, HDDs, SSDs, etc. The communication device 403 communicates with a management server 300. The functions of the vehicle-mounted device 400 are realized through the cooperation of the processor 401 and the storage device 402. Program 405 is a computer program executed by the processor 401. The functions of the vehicle-mounted device 400 can also be realized through the cooperation of the processor 401 executing program 405 and the storage device 402. The program 405 is stored in the storage device 402. Alternatively, the program 405 may also be recorded on a computer-readable recording medium.

[0141] The management server 300 includes one or more processors 301 (hereinafter referred to as processor 301), one or more storage devices 302 (hereinafter referred to as storage devices 302), and a communication device 303. The processor 301 performs various processes. Examples of processors 301 include general-purpose processors, special-purpose processors, CPUs, GPUs, ASICs, FPGAs, integrated circuits, conventional circuits, and / or combinations thereof. The processor 301 may also be referred to as a circuitry or processing circuitry. The storage device 302 stores (saves) various information. Examples of storage devices 302 include volatile memory, non-volatile memory, HDDs, SSDs, etc. The communication device 303 communicates with the on-board units 400 of multiple electric vehicles 10. The functions of the management server 300 are realized through the cooperation of the processor 301 and the storage device 302. Program 305 is a computer program executed by the processor 301. The functions of the management server 300 can also be realized through the cooperation of the processor 301 executing program 305 and the storage device 302. Program 305 is stored in the storage device 302. Alternatively, program 305 may be recorded on a computer-readable recording medium.

[0142] The processor 401 of the vehicle-mounted device 400 and the processor 301 of the management server 300, or a combination thereof, are equivalent to Figure 1One or more processors 101 are shown. Any one or a combination of the storage device 402 of the vehicle-mounted device 400 and the storage device 302 of the management server 300 is equivalent to... Figure 1 One or more storage devices 102 are shown. Any one or a combination of the program 405 of the vehicle-mounted device 400 and the program 305 of the management server 300 is equivalent to... Figure 1 The vehicle management procedure 105 is shown.

[0143] 3-1. The first example

[0144] Figure 11 This is a block diagram illustrating a first example of how the vehicle management system 100 is used. In this first example, the driving state acquisition unit 110, the sound source data management unit 120, the engine sound generation unit 130, the output unit 140, and the passive driving level acquisition unit 150 are all included in the on-board unit 400. The management of simulated engine sound is performed within the electric vehicle 10.

[0145] 3-2. Second case

[0146] Figure 12 This is a block diagram illustrating a second example of how the vehicle management system 100 is used. In this second example, compared to the first example described above, the audio source data management unit 120 is included within the management server 300. The audio source data management unit 120 uniformly manages the basic audio source data 200 used in multiple electric vehicles 10. Therefore, the basic audio source data 200 is associated with a vehicle ID. The audio source data management unit 120 manages the available basic audio source data 200 for each vehicle ID.

[0147] The engine sound generation unit 130 of the vehicle-mounted device 400 downloads the basic audio source data 200 associated with the vehicle ID from the audio source data management unit 120 of the management server 300.

[0148] The passive driving level acquisition unit 150 of the vehicle-mounted device 400 can also upload the set of vehicle ID and passive driving level NEG to the management server 300. The upload frequency is arbitrary. The audio source data management unit 120 of the management server 300 changes the type of available basic audio source data 200 associated with the vehicle ID based on the received passive driving level NEG. For example, as the passive driving level NEG increases, the audio source data management unit 120 reduces the types of available basic audio source data 200. The engine sound generation unit 130 of the vehicle-mounted device 400 downloads the available basic audio source data 200 associated with the vehicle ID from the audio source data management unit 120 of the management server 300.

[0149] Thus, according to the second example, the basic audio source data 200 used in multiple electric vehicles 10 is uniformly managed in the management server 300. This is preferred from the viewpoint of managing the basic audio source data 200.

[0150] 3-3. The Third Case

[0151] Figure 13 This is a block diagram illustrating a third example of how the vehicle management system 100 is used. In this third example, compared to the first example described above, the passive driving level acquisition unit 150 is included in the management server 300. The passive driving level acquisition unit 150 manages the passive driving level NEG associated with multiple electric vehicles 10. Therefore, the passive driving level NEG is associated with the vehicle ID. The passive driving level acquisition unit 150 manages the passive driving level NEG for each vehicle ID.

[0152] The on-board unit 400 uploads a set of vehicle ID and driving status information (DRV) to the management server 300. The upload frequency is arbitrary. The negative driving level acquisition unit 150 of the management server 300 acquires the negative driving level (NEG) associated with the vehicle ID based on the received driving status information (DRV). Furthermore, the negative driving level acquisition unit 150 sends the negative driving level (NEG) to the electric vehicle 10 with that vehicle ID. The on-board unit 400 of the electric vehicle 10 with that vehicle ID performs sound management based on the received negative driving level (NEG).

[0153] According to the third example, the vehicle-mounted device 400 does not need to have a passive driving level acquisition unit 150. Therefore, the storage capacity of the vehicle-mounted device 400 can be saved. In addition, the processing load of the vehicle-mounted device 400 can be reduced. Furthermore, it is not necessary to update the algorithm of the passive driving level acquisition unit 150 in each of the multiple electric vehicles 10, but can be done simply all at once.

[0154] 3-4. Fourth case

[0155] Figure 14 This is a block diagram illustrating a fourth example of how the vehicle management system 100 is used. In this fourth example, compared to the first example described above, the audio source data management unit 120 and the negative driving accuracy acquisition unit 150 are included in the management server 300. That is, the fourth example is a combination of the second and third examples described above.

[0156] 4. Application of electric vehicles with manual mode (MT mode)

[0157] The electric motor used as the power source in a typical electric vehicle (EV) has significantly different torque characteristics compared to the internal combustion engine used in a conventional vehicle (CV). Due to this difference in torque characteristics, CVs require a transmission, whereas electric vehicles typically do not. Furthermore, typical electric vehicles lack a manual transmission (MT) where the driver manually changes gear ratios. Therefore, the driving experience differs considerably between driving a conventional vehicle with an MT and driving an electric vehicle.

[0158] On the other hand, the torque of an electric motor can be relatively easily controlled by adjusting the applied voltage and excitation. Therefore, by implementing appropriate control, the desired torque characteristics can be obtained within the operating range of the electric motor. Utilizing this feature, the torque of an electric vehicle can be controlled to simulate the torque characteristics unique to a manual transmission (MT) vehicle. Furthermore, a simulated gear shifter can be installed in the electric vehicle to allow the driver to experience the driving feel of a MT vehicle. Thus, a MT vehicle can be simulated within an electric vehicle.

[0159] In other words, the electric vehicle controls the motor output in a manner that simulates the driving characteristics (torque characteristics) unique to a manual transmission (MT) vehicle. The driver operates a simulated gearshift to perform simulated manual shifting operations. In response to the driver's simulated manual shifting operations, the electric vehicle changes its driving characteristics (torque characteristics) in a manner that mimics that of an MT vehicle. Thus, the driver of the electric vehicle can experience a feeling similar to driving a MT vehicle. Hereinafter, this motor control mode used to simulate the driving characteristics and manual shifting operations of an MT vehicle will be referred to as "manual mode" or "MT mode."

[0160] The electric vehicle 10 according to this disclosure can have a manual mode (MT mode). In MT mode, the electric vehicle 10 generates a simulated engine sound corresponding to the driver's driving operation and outputs the simulated engine sound via a speaker 70. Not only is the driving operation of the MT vehicle reproduced, but also the engine sound of the MT vehicle is reproduced, thus improving the satisfaction of drivers who require a realistic driving experience.

[0161] The following describes a structural example of an electric vehicle 10 equipped with a manual mode (MT mode).

[0162] 4-1. First Construction Example (Sequence Shifter)

[0163] Figure 15This is a block diagram illustrating a first structural example of the power control system of the electric vehicle 10 according to this embodiment. The electric vehicle 10 includes an electric motor 44, a battery 46, and a converter 42. The electric motor 44 is a power unit for driving. The battery 46 stores electrical energy that drives the electric motor 44. That is, the electric vehicle 10 is a battery electric vehicle (BEV) that uses the electrical energy stored in the battery 46 for driving. The converter 42 converts the DC power input from the battery 46 during acceleration into driving power for the electric motor 44. In addition, the converter 42 converts the regenerative power input from the electric motor 44 into DC power during deceleration and charges the battery 46.

[0164] The electric vehicle 10 is equipped with an accelerator pedal 22 for the driver to input acceleration requirements for the electric vehicle 10. An accelerator position sensor 32 for detecting the accelerator opening is provided on the accelerator pedal 22.

[0165] The electric vehicle 10 is equipped with a sequential shifter 24. The sequential shifter 24 can be a paddle shifter or a lever-type analog shifter.

[0166] A paddle shifter is a virtual shifter, distinct from a traditional paddle shifter. It has a similar structure to the paddle shifters found in clutchless manual transmission (MT) vehicles. The paddle shifter is mounted on the steering wheel. It includes upshift and downshift switches that determine the operating position. The upshift switch sends an upshift signal 34u when pulled forward, and the downshift switch sends a downshift signal 34d when pulled forward.

[0167] On the other hand, the lever-type simulated shifter, like the paddle shifter, is a virtual shifter different from the original shifter. The lever-type simulated shifter has a similar structure to the lever-type shifter found in clutchless MT vehicles. The lever-type simulated shifter mechanism outputs an upshift signal 34u by tilting the shift lever forward and a downshift signal 34d by tilting the shift lever backward.

[0168] Wheel speed sensors 36 are provided on the wheels 26 of the electric vehicle 10. The wheel speed sensors 36 are used as vehicle speed sensors to detect the speed of the electric vehicle 10. In addition, a rotation speed sensor 38 is provided on the electric motor 44 to detect its rotation speed.

[0169] The electric vehicle 10 includes a control device 50. The control device 50 is typically an electronic control unit (ECU) mounted on the electric vehicle 10. The control device 50 can also be a combination of multiple ECUs. The control device 50 includes an interface, memory, and a processor. An in-vehicle network is connected to the interface. The memory includes RAM for temporarily recording data and ROM for storing programs executable by the processor and various data associated with the programs. The program consists of multiple instructions. The processor reads the program and data from the memory and executes them, generating control signals based on signals obtained from various sensors.

[0170] For example, control unit 50 controls motor 44 via PWM control of converter 42. Signals from accelerometer position sensor 32, sequential shifter 24 (which serves as upshift and downshift switches in the case of a paddle shifter), wheel speed sensor 36, and speed sensor 38 are input to control unit 50. Control unit 50 processes these signals and calculates the motor torque command value for PWM control of converter 42.

[0171] The control device 50 includes an automatic mode (EV mode) and a manual mode (MT mode) as control modes. The automatic mode is the normal control mode for driving the electric vehicle 10 as a regular electric vehicle. The automatic mode is programmed to continuously change the output of the electric motor 44 based on the operation of the accelerator pedal 22. On the other hand, the manual mode is the control mode for driving the electric vehicle 10 like a manual transmission (MT) vehicle. The manual mode is programmed to change the output characteristics of the electric motor 44 in response to upshifting and downshifting operations relative to the accelerator pedal 22 based on the sequential shifter 24. In other words, the manual mode is a control mode capable of changing the output of the electric motor 44 in response to driving operations of vehicle components other than the accelerator pedal 22 and brake pedal. The automatic mode (EV mode) and the manual mode (MT mode) are switchable.

[0172] The control device 50 includes an automatic mode torque calculation unit 54 and a manual mode torque calculation unit 56. Each unit 54 and 56 can be a separate independent ECU, or the function of an ECU can be obtained by a processor executing a program recorded in memory.

[0173] The automatic mode torque calculation unit 54 has the function of calculating the motor torque when controlling the motor 44 in automatic mode. The automatic mode torque calculation unit 54 stores a motor torque command map. The motor torque command map is determined based on the accelerator opening and the rotational speed of the motor 44. Signals from the accelerator position sensor 32 and the speed sensor 38 are input to the parameters of the motor torque command map. The motor torque corresponding to these signals is output from the motor torque command map. Therefore, in automatic mode, even if the driver operates the sequence shifter 24, this operation will not be reflected in the motor torque.

[0174] The manual mode torque calculation unit 56 has an MT vehicle model. The MT vehicle model is used to calculate the drive wheel torque that should be obtained by operating the accelerator pedal 22 and the sequential shifter 24 when the electric vehicle 10 is assumed to be an MT vehicle.

[0175] Reference Figure 16 The MT vehicle model included in the manual mode torque calculation unit 56 is explained. For example... Figure 16 As shown, the MT vehicle model includes an engine model 561, a clutch model 562, and a transmission model 563. Furthermore, the engine, clutch, and transmission, virtually implemented through the MT vehicle model, are respectively referred to as a virtual engine, a virtual clutch, and a virtual transmission. In engine model 561, the virtual engine is modeled. In clutch model 562, the virtual clutch is modeled. In transmission model 563, the virtual transmission is modeled.

[0176] Engine model 561 calculates the virtual engine speed Ne and the virtual engine output torque Teout. The virtual engine speed Ne is calculated based on the wheel speed Nw, the combined reduction ratio R, and the slip ratio Rslip of the virtual clutch. For example, the virtual engine speed Ne is represented by the following equation (1).

[0177] Equation (1): Ne = Nw × R / (1 - Rslip)

[0178] The virtual engine output torque Teout is calculated based on the virtual engine speed Ne and the accelerator opening Pap. In the calculation of the virtual engine output torque Teout, as follows... Figure 16 As shown, a mapping is used that defines the relationship between accelerator opening Pap, virtual engine speed Ne, and virtual engine output torque Teout. In this mapping, each accelerator opening Pap is assigned a virtual engine output torque Teout relative to the virtual engine speed Ne. Figure 16The torque characteristics shown can be set to the characteristics of a hypothetical gasoline engine or a hypothetical diesel engine. Alternatively, the characteristics can be set to those of a naturally aspirated engine or a turbocharged engine.

[0179] Clutch model 562 calculates the torque transmission gain k. The torque transmission gain k is used to calculate the torque transmission degree of the virtual clutch corresponding to the virtual clutch opening Pc. The virtual clutch opening Pc is typically 0%, temporarily opening to 100% in conjunction with the switching of virtual gear stages in the virtual transmission. Clutch model 562 has the following characteristics: Figure 16 The mapping shown is used. In this mapping, the torque transfer gain k is assigned to the virtual clutch opening Pc. Figure 16 In the model, Pc0 corresponds to the position where the virtual clutch opening Pc is 0%, and Pc3 corresponds to the position where the virtual clutch opening Pc is 100%. The ranges from Pc0 to Pc1 and from Pc2 to Pc3 are the dead zones where the torque transfer gain k does not change according to the virtual clutch opening Pc. Clutch model 562 uses the torque transfer gain k to calculate the clutch output torque Tcout. The clutch output torque Tcout is the torque output from the virtual clutch. For example, the clutch output torque Tcout is given by the product of the virtual engine output torque Teout and the torque transfer gain k (Tcout = Teout × k).

[0180] Additionally, clutch model 562 calculates the slip ratio Rslip. The slip ratio Rslip is used to calculate the virtual engine speed Ne in engine model 561. In the calculation of the slip ratio Rslip, similar to the torque transmission gain k, a mapping of the slip ratio Rslip to the virtual clutch opening Pc can be used.

[0181] The transmission model 563 calculates the gear ratio (gear shift ratio) r. The gear ratio r is determined by the virtual gear stage GP in the virtual transmission. Upon receiving an upshift operation from the sequential shifter 24, the virtual gear stage GP moves up one gear. Conversely, upon receiving a downshift operation from the sequential shifter 24, the virtual gear stage GP moves down one gear. The transmission model 563 has the following characteristics: Figure 16The mapping is shown. In this mapping, the virtual gear stage GP is assigned a gear ratio r such that the larger the virtual gear stage GP, the smaller the gear ratio r. The transmission model 563 uses the gear ratio r obtained from the mapping and the clutch output torque Tcout to calculate the transmission output torque Tgout. For example, the transmission output torque Tgout is given by the product of the clutch output torque Tcout and the gear ratio r (Tgout = Tcout × r). The transmission output torque Tgout varies discontinuously according to the switching of the gear ratio r. This discontinuous variation of the transmission output torque Tgout produces shift shocks, exhibiting the potential of vehicles with stepped transmissions.

[0182] The MT vehicle model uses a specified reduction ratio rr to calculate the drive wheel torque Tw. The reduction ratio rr is a fixed value determined by the mechanical structure from the virtual transmission to the drive wheels. Multiplying the reduction ratio rr by the gear ratio r yields the aforementioned combined reduction ratio R. The MT vehicle model calculates the drive wheel torque Tw based on the transmission output torque Tgout and the reduction ratio rr. For example, the drive wheel torque Tw is given by the product of the transmission output torque Tgout and the reduction ratio rr (Tw = Tgout × rr).

[0183] The control unit 50 converts the drive wheel torque Tw calculated from the MT vehicle model into the required motor torque Tm. The required motor torque Tm is the motor torque required to achieve the drive wheel torque Tw calculated from the MT vehicle model. In the conversion from drive wheel torque Tw to required motor torque Tm, a reduction ratio from the output shaft of the motor 44 to the drive wheel is used. Furthermore, the control unit 50 controls the motor 44 according to the required motor torque Tm by controlling the converter 42.

[0184] Figure 17 This graph compares the torque characteristics of motor 44 implemented using motor control in an MT vehicle model with the torque characteristics of motor 44 implemented using conventional motor control in an electric vehicle (EV). Based on the motor control using the MT vehicle model, such as... Figure 17 As shown, the torque characteristics (solid line in the figure) simulating the torque characteristics of a manual transmission vehicle can be achieved based on the virtual gear stages set by the sequential shifter 24. Furthermore, in Figure 17 In the middle, the number of gear stages is 6.

[0185] 4-2. Example of the second structure

[0186] Figure 18This is a block diagram illustrating a second structural example of the power control system of the electric vehicle 10 according to this embodiment. Here, only the configuration different from the first configuration example described above will be described. Specifically, in the second structural example, the electric vehicle 10 has a simulated gear shift lever (simulated gear shifting device) 27 and a simulated clutch pedal 28 instead of the sequential gear shifter 24 provided in the first structural example. The simulated gear shift lever 27 and the simulated clutch pedal 28 are simply dummy components different from the original gear shift lever and clutch pedal.

[0187] The simulated gear shift lever 27 has the structure of a gear shift lever found in a manual transmission (MT) vehicle. The configuration and operation of the simulated gear shift lever 27 are identical to those of an actual MT vehicle. The simulated gear shift lever 27 has positions corresponding to gears such as 1st, 2nd, 3rd, 4th, 5th, 6th, reverse, and neutral. A gear position sensor 27a is provided on the simulated gear shift lever 27, which detects the gear position by determining the location of the simulated gear shift lever 27.

[0188] The simulated clutch pedal 28 has the structure of a clutch pedal found in a manual transmission (MT) vehicle. The configuration and operating feel of the simulated clutch pedal 28 are identical to those of an actual MT vehicle. The simulated clutch pedal 28 is operated when the simulated shift lever 27 is used. That is, the driver depresses the simulated clutch pedal 28 when they wish to change the gear position using the simulated shift lever 27, and releases the pedal when the gear position change is complete, allowing the simulated clutch pedal 28 to return to its original position. The simulated clutch pedal 28 is equipped with a clutch position sensor 28a for detecting the amount of depressurization of the simulated clutch pedal 28.

[0189] Signals from the accelerator position sensor 32, gear position sensor 27a, clutch position sensor 28a, wheel speed sensor 36, and speed sensor 38 are input to the control unit 50. The control unit 50 processes these signals and calculates the motor torque command value for PWM control of the converter 42.

[0190] Similar to the first structural example described above, the control device 50 includes an automatic mode and a manual mode as control modes. The automatic mode is programmed to continuously change the output of the electric motor 44 based on the operation of the accelerator pedal 22. On the other hand, the manual mode is a control mode for driving the electric vehicle 10 like a manual transmission (MT) vehicle. The manual mode is programmed to change the output and output characteristics of the electric motor 44 in response to the operation of the accelerator pedal 22 based on the operation of the simulated clutch pedal 28 and the simulated gear shift lever (simulated gear shifting device) 27. In other words, the manual mode is a control mode capable of changing the output of the electric motor 44 in response to driving operations of vehicle components other than the accelerator pedal 22 or the brake pedal.

[0191] The vehicle model and manual mode torque calculation unit 56 are equipped with Figure 16 The vehicle model shown is the same. However, the virtual clutch opening Pc is replaced by the amount of pressure applied to the virtual clutch pedal 28 detected by the clutch position sensor 28a. Additionally, the virtual gear shift GP is determined by the position of the simulated gear shift lever 27 detected by the gear position sensor 27a.

[0192] 5. The management of driving characteristics for dangerous driving has been taken into consideration.

[0193] The electric vehicle 10 in this embodiment can also have a simulation mode that simulates the driving characteristics of a virtual vehicle.

[0194] For example, as explained in section 4 above, the electric vehicle 10 may also have a manual mode (MT mode) that simulates the driving characteristics of a MT vehicle. In this case, the virtual vehicle is an MT vehicle. The simulation mode includes the manual mode (MT mode).

[0195] As another example, electric vehicle 10 could also have an EV mode that simulates the driving characteristics of a different type of electric vehicle than electric vehicle 10. In this case, the virtual vehicle is a different type of electric vehicle than electric vehicle 10.

[0196] The vehicle management system 100 described in this embodiment can also change the options for virtual vehicles in simulation mode based on the level of negative driving (NEG). For example, as the level of negative driving (NEG) increases, the vehicle management system 100 reduces the number of virtual vehicle options in simulation mode.

[0197] Figure 19 This is a block diagram illustrating another example of the functional structure of the vehicle management system 100. The vehicle management system 100 includes a driving state acquisition unit 110, a passive driving level acquisition unit 150, and a virtual vehicle management unit 170 as functional blocks. These functional blocks can also be implemented, for example, through the cooperation of a processor 101 executing the vehicle management program 105 and a storage device 102.

[0198] The driving status acquisition unit 110, the passive driving level acquisition unit 150, and the user interface 160 are the same as in the above embodiment.

[0199] The Virtual Vehicle Management Unit 170 manages virtual vehicle model data 270, which represents the model of the virtual vehicle, the simulated object in simulation mode. For example, in the case of manual mode (MT mode) simulating the driving characteristics of a manual transmission (MT) vehicle, the virtual vehicle model data 270 includes... Figure 16 The MT vehicle model shown is as follows (engine model 561, clutch model 562, and transmission model 563). If the MT vehicle being simulated is different, then the MT vehicle model, i.e., the virtual vehicle model data 270, will also be different. Figure 17The driving characteristics (torque characteristics) shown are also different.

[0200] The Negative Driving Level Acquisition Unit 150 outputs the Negative Driving Level NEG to the Virtual Vehicle Management Unit 170. The Virtual Vehicle Management Unit 170 changes the type of available virtual vehicle model data 270 based on the Negative Driving Level NEG. The available virtual vehicle model data 270 may be provided, for example, from a management server. The change in the type of available virtual vehicle model data 270 is equivalent to the change in the options for available virtual vehicles in simulation mode.

[0201] For example, as the level of negative driving (NEG) increases, the virtual vehicle management unit 170 reduces the variety of available virtual vehicle model data 270. In other words, as the level of negative driving (NEG) increases, the virtual vehicle management unit 170 reduces the number of virtual vehicle options available in simulation mode. When changing the virtual vehicle options based on the level of negative driving (NEG), the options can also be changed from the default options. The default options are the normal options when the level of negative driving (NEG) is not considered.

[0202] The user (driver) of the electric vehicle 10 can specify a desired virtual vehicle model from a variety of virtual vehicle model data 270 via the user interface 160. The control device 50 uses the virtual vehicle model data 270 specified by the user to simulate the driving characteristics of the virtual vehicle. That is, the user of the electric vehicle 10 can specify a desired option from the virtual vehicle options via the user interface 160.

[0203] As explained above, the electric vehicle 10 has a simulation mode that simulates the driving characteristics of a virtual vehicle. Furthermore, the options for the virtual vehicle available in the simulation mode change according to the negative driving level NEG, which indicates the degree of dangerous driving by the electric vehicle 10. Through these changes in the virtual vehicle options, the driver can become aware of dangerous driving. As a result, the driver can control and suppress dangerous driving.

[0204] The number of virtual vehicle options also decreases as the level of passive driving (NEG) increases. This provides a strong incentive for drivers who want to enjoy the simulation mode to avoid dangerous driving, thus further suppressing dangerous driving.

[0205] In addition, the above Figures 11-14 The audio data management department 120 was replaced by the virtual vehicle management department 170.

[0206] 6. Combination

[0207] Combinations of Parts 2 and 5 above are also possible. That is, considering dangerous driving, the vehicle management system 100 can perform both the sound management described in Part 2 and the driving characteristic management described in Part 5.

[0208] [Explanation of reference numerals in the attached figures]

[0209] 10… Electric vehicle, 11… Sensor, 44… Electric motor, 70… Speaker, 100… Vehicle management system, 110… Operation status acquisition unit, 120… Audio source data management unit, 130… Engine sound generation unit, 140… Output unit, 150… Negative driving level acquisition unit, 160… User interface, 170… Virtual vehicle management unit, 200… Basic audio source data, 270… Virtual vehicle model data, 300… Management server, 400… Onboard device, DRV… Operation status information, ES… Engine sound data, NEG… Negative driving level.

Claims

1. A vehicle management system applied to an electric vehicle, wherein the electric vehicle uses an electric motor as a power unit for driving, wherein, The vehicle management system includes one or more processors configured to generate sound and output the sound through speakers mounted on the electric vehicle. The one or more processors are further configured to: Obtain driving status information representing the driving state of the electric vehicle. Based on the driving state information, a degree of passive driving, representing the extent of dangerous driving by the electric vehicle, is obtained. The sound may be changed and / or the options for the sound may be changed depending on the level of passive driving.

2. The vehicle management system according to claim 1, wherein, The one or more processors are configured to reduce the audibility of the sound as the degree of passive driving increases.

3. The vehicle management system according to claim 1, wherein, The one or more processors are configured to increase the noise or unwanted sound components contained in the sound as the degree of passive driving increases.

4. The vehicle management system according to claim 1, wherein, The one or more processors are configured to mute the sound or increase the sound pressure level of the sound if the degree of passive driving exceeds a threshold.

5. The vehicle management system according to claim 1, wherein, The one or more processors are configured to change at least one of the timbre, tone quality, sound pressure level, and range of the sound according to the degree of passive driving.

6. The vehicle management system according to claim 1, wherein, The one or more processors are configured to reduce the option of the sound as the level of passive driving increases.

7. The vehicle management system according to claim 1, wherein, The driving state of the electric vehicle includes at least one of the following: presence or absence of speed limit, speed, acceleration, deceleration, steering speed, inter-vehicle distance, TTC (Time-To-Collision), distance to surrounding objects, frequency of lane changes, and state of lane changes.

8. The vehicle management system according to claim 1, wherein, The sound is a simulated engine sound.

9. The vehicle management system according to any one of claims 1-8, wherein, The electric vehicle has a simulation mode that simulates the driving characteristics of a virtual vehicle.

10. The vehicle management system according to claim 9, wherein, The one or more processors are also configured to vary the options for the virtual vehicle that can be used in the simulation mode, depending on the degree of passive driving.

11. The vehicle management system according to claim 9, wherein, The virtual vehicle is a vehicle with a manual transmission. The simulation mode includes a manual mode that simulates the driving characteristics of the vehicle with the manual transmission.

12. The vehicle management system according to claim 11, wherein, The electric vehicle is equipped with an accelerator pedal and a sequential gear shifter. In the manual mode, the electric vehicle is configured such that the output characteristics of the electric motor, in relation to the operation of the accelerator pedal, change according to the shifting operation of the sequential shifter.

13. The vehicle management system according to claim 11, wherein, The electric vehicle is equipped with an accelerator pedal, a simulated clutch pedal, and a simulated gear shifting device. The simulated clutch pedal is operated when the simulated gear shifting device is used. In the manual mode, the electric vehicle is configured such that the output of the electric motor, which is opposite to the operation of the accelerator pedal, varies according to the operation of the simulated clutch pedal and the operation of the simulated gear shifting device.

14. An electric vehicle that uses an electric motor as a power unit for driving, wherein, The electric vehicle includes one or more processors configured to generate sound and output the sound through speakers mounted on the electric vehicle. The one or more processors are further configured to: Obtain driving status information representing the driving state of the electric vehicle. Based on the driving state information, a degree of passive driving, representing the extent of dangerous driving by the electric vehicle, is obtained. The sound may be changed and / or the options for the sound may be changed depending on the level of passive driving.

15. A vehicle management system applied to an electric vehicle, wherein the electric vehicle uses an electric motor as a power unit for driving, wherein... The electric vehicle has a simulation mode that simulates the driving characteristics of a virtual vehicle. The vehicle management system has one or more processors. The one or more processors are configured as follows: Obtain driving status information representing the driving state of the electric vehicle. Based on the driving state information, a degree of passive driving, representing the extent of dangerous driving by the electric vehicle, is obtained. The options for the virtual vehicle that can be used in the simulation mode vary depending on the level of passive driving.

16. The vehicle management system according to claim 15, wherein, The one or more processors are configured to reduce the number of virtual vehicle options available in the simulation mode as the level of passive driving increases.

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