WO2022007235A1 - Système informatique nuage-périphérie pour véhicule électrique pur - Google Patents

Système informatique nuage-périphérie pour véhicule électrique pur Download PDF

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Publication number
WO2022007235A1
WO2022007235A1 PCT/CN2020/122406 CN2020122406W WO2022007235A1 WO 2022007235 A1 WO2022007235 A1 WO 2022007235A1 CN 2020122406 W CN2020122406 W CN 2020122406W WO 2022007235 A1 WO2022007235 A1 WO 2022007235A1
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WIPO (PCT)
Prior art keywords
information
preprocessing
cloud computing
raspberry
edge
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PCT/CN2020/122406
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English (en)
Chinese (zh)
Inventor
程涛
刘远鹏
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深圳技术大学
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Publication of WO2022007235A1 publication Critical patent/WO2022007235A1/fr

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
    • B60L3/12—Recording operating variables ; Monitoring of operating variables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/16—Information or communication technologies improving the operation of electric vehicles

Definitions

  • the invention relates to a communication control technology, in particular to an edge-cloud computing system of a pure electric vehicle.
  • pure electric vehicles are the main trend of future automobile development.
  • the core technologies of pure electric vehicles include pure electric vehicle technology, motor drive and control technology, battery and management technology, and a series of safety protection and lightweight technologies. It is an extremely important part.
  • the stability of the system and its performance directly affect the safe driving of pure electric vehicles, and are inextricably linked with the safety of people's lives and property. Therefore, how to judge whether a pure electric vehicle is safe and reliable depends on the stability of various technologies and systems. In order to judge the reliability of a pure electric vehicle, the monitoring and evaluation of various vehicle status data information has become the most important. one of the sections.
  • the technical problem to be solved by the present invention is: to provide an edge-cloud computing system for pure electric vehicles, which has a more stable monitoring system, so as to ensure the reliability of monitoring the state of the vehicle.
  • an edge-cloud computing system for pure electric vehicles including a cloud computing terminal and at least two edge terminals;
  • the edge terminal is used for acquiring car information and preprocessing the car information to generate multi-physical domain information
  • the cloud computing terminal is connected to the edge terminal, used to control each edge terminal, and also used to fuse and manage the multi-physical domain information;
  • the vehicle information includes information of vehicle motion, information of vehicle battery and information of vehicle motor.
  • the edge end includes a first sensor and a first Raspberry Pi;
  • the first sensor for monitoring the speed and/or acceleration of the vehicle to generate first monitoring information
  • the first Raspberry Pi is connected to the first sensor, and is used for preprocessing the first monitoring information to generate first preprocessing information.
  • edge end includes a second sensor and a second Raspberry Pi;
  • the second sensor is used to monitor the current and/or voltage of the vehicle battery to generate second monitoring information
  • the second Raspberry Pi is connected to the second sensor, and is used for preprocessing the second monitoring information to generate second preprocessing information.
  • the edge end includes a third sensor and a third Raspberry Pi;
  • the third sensor is used to monitor the motor state of the vehicle and generate third monitoring information
  • the third Raspberry Pi connected to the third sensor, for preprocessing the third monitoring information to generate third preprocessing information
  • the third monitoring information includes motor torque and motor transmission ratio.
  • the edge end includes a fourth sensor and a fourth Raspberry Pi;
  • the fourth sensor is used to acquire the image of the car and generate fourth monitoring information
  • the fourth Raspberry Pi connected to the fourth sensor, for preprocessing the fourth monitoring information to generate fourth preprocessing information
  • the image of the car includes an image of the interior of the car and/or an image of the exterior of the car.
  • the first Raspberry Pi, the second Raspberry Pi, the third Raspberry Pi and the fourth Raspberry Pi are respectively connected to the cloud computing terminal, and respectively transmit the first preprocessing information , the second preprocessing information, the third preprocessing information, and the fourth preprocessing information arrive at the cloud computing terminal.
  • the cloud computing terminal includes a data fusion module and a server module;
  • the data fusion module is used for connecting the first Raspberry Pi, the second Raspberry Pi, the third Raspberry Pi and the fourth Raspberry Pi, and for the first preprocessing information, all the performing multi-physical domain fusion on the second preprocessing information, the third preprocessing information and the fourth preprocessing information;
  • the server module is connected with the data fusion module and is used for managing the multi-physical domain information.
  • the server module is provided with a deep learning unit for performing neural network computation on the multi-physical domain information to obtain the first preprocessing information, the second preprocessing information, and the third preprocessing information information and the weight of the fourth preprocessing information.
  • the cloud computing terminal also includes a user access module and a service management module;
  • the user access module connected with the server module, is used for issuing user instructions and receiving feedback information
  • the service management module is connected with the server module, and is used for invoking the multi-physical domain information, managing the server module, and sending feedback information in response to the user instruction.
  • the edge terminal in order to ensure the smooth operation of the electric vehicle, the edge terminal is used to monitor the electric vehicle from the three positions of the vehicle motion state, the vehicle battery and the vehicle motor, and by setting different sensors to generate redundant information, This enhances the accuracy of monitoring.
  • these redundant information require a large amount of computation, and the computing power at the edge is relatively low, so they are only used to preprocess the car information, so as to avoid jamming and ensure the overall stability. Therefore, in the present invention, a two-layer information processing structure is set up, the cloud computing terminal is used to control the computing resources of the edge terminal, and the multi-physical domain information is fused and managed, so as to better control the overall information and ensure the stability of the overall system. sex.
  • FIG. 1 is a structural diagram of a side-cloud computing system of a pure electric vehicle in a first embodiment of the present invention
  • FIG. 2 is a structural diagram of a side-cloud computing system of a pure electric vehicle in a second embodiment of the present invention
  • FIG. 3 is a structural diagram of a cloud computing terminal of a pure electric vehicle in a third embodiment of the present invention.
  • FIG. 1 is a structural diagram of an edge-cloud computing system of a pure electric vehicle according to a first embodiment of the present invention.
  • the present application provides an edge-cloud computing system for a pure electric vehicle, including a cloud computing terminal 200 and at least two edge terminals 100;
  • the edge terminal 100 is used for acquiring car information and preprocessing the car information to generate multi-physical domain information
  • the cloud computing terminal 200 is connected to the edge terminal 100 and is used to control each edge terminal 100, and is also used to fuse and manage multi-physical domain information;
  • the car information includes the information of the car movement, the information of the car battery and the information of the car motor.
  • the edge terminal 100 is used to monitor the electric vehicle from the three positions of the vehicle motion state, the vehicle battery and the vehicle motor, and generate redundant information by setting different sensors. This enhances the accuracy of monitoring.
  • this redundant information requires a large amount of computation, and the computing capability of the edge terminal 100 is relatively low, so it is only used to preprocess the car information, so as to avoid jamming and ensure the overall stability. Therefore, in the present invention, a two-layer information processing structure is set up, the cloud computing terminal 200 is used to control the computing resources of the edge terminal 100, and the multi-physical domain information is fused and managed, so as to better control the overall information and ensure the overall system stability.
  • FIG. 2 is a structural diagram of the edge-cloud computing system of the pure electric vehicle in the second embodiment of the present invention.
  • the edge terminal 100 includes a first sensor 111 and a first Raspberry Pi 112 ;
  • the first sensor 111 is used for monitoring the speed and/or acceleration of the vehicle to generate first monitoring information.
  • the first Raspberry Pi 112 is connected to the first sensor 111, and is used for preprocessing the first monitoring information to generate the first preprocessing information.
  • first sensors 111 there may be multiple first sensors 111, which are respectively placed at different positions on the vehicle body.
  • the first case it is only necessary to monitor the speed of the car body to determine whether the car is running, and to know the normal operation of the car, so as to evaluate the overall operation of the car .
  • the acceleration of the vehicle is mainly used to obtain the changing trend of the vehicle body.
  • the problem of the vehicle body can be known at the first time.
  • the first sensor 111 is mainly installed on the vehicle body to monitor the operation of the vehicle.
  • the first Raspberry Pi 112 is specially used for preprocessing the first monitoring information, and the speed can be integrated and classified to form multiple sets, thereby reducing the calculation amount of the cloud computing terminal 200 .
  • the edge terminal 100 includes a second sensor 121 and a second Raspberry Pi 122;
  • the second sensor 121 is used to monitor the current and/or voltage of the vehicle battery to generate second monitoring information.
  • the battery has certain advantages to judge the state of the car, because the battery can intuitively reflect the state of the electric vehicle. Any damage to the circuit structure of the car can be reflected in the circuit of the battery.
  • the only source of power for electric vehicles is the battery. If the current and voltage are monitored separately, it may happen to encounter the corresponding situation due to the coincidence of a certain circuit. Therefore, monitoring these two parameters at the same time can monitor the circuit status more accurately. The monitoring of the current or voltage parameter alone can reduce the amount of calculation required, so that this data can be obtained more quickly.
  • the second Raspberry Pi 122 is connected to the second sensor 121 for preprocessing the second monitoring information to generate the second preprocessing information.
  • each second Raspberry Pi 122 can be connected to a plurality of second sensors 121, and a second Raspberry Pi 122 can preprocess the second monitoring information of the plurality of second sensors 121, so as to reduce the The computing amount of the cloud computing terminal 200 .
  • the edge terminal 100 includes a third sensor 131 and a third Raspberry Pi 132;
  • the third sensor 131 is used to monitor the motor state of the vehicle and generate third monitoring information, wherein the third monitoring information includes the motor torque and the motor transmission ratio.
  • Motor torque and motor gear ratio can be used to measure the state of the motor.
  • the third monitoring information can cooperate with the first monitoring information to monitor the state of the car; it can also cooperate with the second monitoring information to monitor the state of the car.
  • the third Raspberry Pi 132 is connected to the third sensor 131 for preprocessing the third monitoring information to generate third preprocessing information. It can be understood that the third Raspberry Pi 132 mainly preprocesses the sensor data of the motor, and the sensor data of the motor changes greatly, so the third Raspberry Pi 132 needs to be preprocessed to reduce The computing amount of the cloud computing terminal 200 .
  • the edge terminal 100 includes a fourth sensor 141 and a fourth Raspberry Pi 142;
  • the fourth sensor 141 is used for acquiring an image of the car and generating fourth monitoring information.
  • the fourth Raspberry Pi 142 is connected to the fourth sensor 141, and is used for preprocessing the fourth monitoring information to generate fourth preprocessing information.
  • the fourth sensor 141 in the above can be an industrial camera or a similar tool such as a driving recorder, and the fourth monitoring information is essentially image information, and the image information of the car can be intuitively seen through the fourth monitoring information.
  • the image of the car may include external information of the car, and may also include internal information of the car.
  • the external information of the car is helpful for the cloud computing terminal 200 to monitor the car, and the internal information of the car is helpful for observing the state of each structure of the car.
  • the fourth sensor 141 is essentially a sensor for image processing.
  • the first Raspberry Pi 112, the second Raspberry Pi 122, the third Raspberry Pi 132, and the fourth Raspberry Pi 142 are respectively connected to the cloud computing terminal 200, and transmit the first preprocessing information, the second Raspberry Pi respectively The preprocessing information, the third preprocessing information, and the fourth preprocessing information arrive at the cloud computing terminal 200 .
  • the information processed by the first Raspberry Pi 112, the second Raspberry Pi 122, the third Raspberry Pi 132 and the fourth Raspberry Pi 142 belongs to information of different physical domains, and this The four types of Raspberry Pi belong to parallel computing units. These four types of Raspberry Pi directly send the information to the cloud computing terminal 200, which reduces the transmission steps and increases the transmission path, thereby avoiding information transmission errors and data loss. In this case, the efficiency of data transmission can be guaranteed.
  • the cloud computing terminal 200 includes a data fusion module 210 and a server module 220;
  • the data fusion module 210 is used for connecting the first Raspberry Pi 112, the second Raspberry Pi 122, the third Raspberry Pi 132 and the fourth Raspberry Pi 142, and for the first preprocessing information, the second preprocessing information, The third preprocessing information and the fourth preprocessing information perform multi-physical domain fusion;
  • the server module 220 connected with the data fusion module 210, is used for managing multi-physical domain information.
  • the data fusion module 210 may perform data fusion on the information of the four physical domains, thereby generating multi-physical domain information. It should be understood that when the sensor information of multiple physical domains is fused, the multi-physical domain information fusion is to synthesize the partial incomplete observations provided by multiple sensors distributed in different locations, and eliminate the possibility of information between multiple sensors. The existing redundancies and contradictions should be complemented to reduce their uncertainty, so as to form a relatively complete and consistent perception description of the system environment, thereby improving the rapidity and correctness of intelligent system decision-making, planning and response, while reducing its decision-making risk.
  • the technology based on multi-physical domain information fusion has three advantages:
  • the monitoring accuracy of the system is improved. Extending from the traditional single physical domain to multiple physical domains, data fusion between the same and different physical domains reduces the interference of noise and improves the accuracy of the system.
  • the monitoring area of the system has been expanded. Compared with the traditional sensor layout, the extensive distribution of the edge end 100 covers a larger area, and can monitor more state parameters of the locomotive and vehicle.
  • the server module 220 is provided with a deep learning unit, which is used to perform neural network calculation on the multi-physical domain information to obtain the weights of the first preprocessing information, the second preprocessing information, the third preprocessing information and the fourth preprocessing information.
  • the weights of the first preprocessing information, the second preprocessing information, the third preprocessing information and the fourth preprocessing information also determine the number of Raspberry Pis corresponding to the corresponding sensors. Raspberry Pi should also be more,
  • one cloud computing terminal 200 is connected to multiple edge terminals 100, and the computing data of these edge terminals 100 will be transmitted to the corresponding cloud computing terminal 200 for processing.
  • heterogeneous sensor data is collected and trained to obtain optimal weights, which can greatly improve the accuracy of data results and reduce measurement errors.
  • FIG. 3 is a structural diagram of a cloud computing terminal 200 of a pure electric vehicle in a third embodiment of the present invention.
  • the cloud computing terminal 200 further includes a user access module 230 and a service management module 240 .
  • the user access module 230 is connected with the server module 220, and is used for issuing user instructions and receiving feedback information.
  • the service management module 240 connected with the server module 220, is used for invoking the multi-physical domain information, and the management server module 220 sends feedback information in response to user instructions.
  • the user access module 230 may be any mobile terminal such as a mobile phone, or may be other modules on the vehicle body that transmit information.
  • the service management module 240 can view the real-time running state of the vehicle, such as information such as the driving speed and acceleration, the battery state, and the real-time working condition of the drive motor.
  • edge-cloud computing system of pure electric vehicles functions such as data partition processing, data exchange in adjacent areas and long-distance data interaction can be realized, and the spare computing power of vehicles in the network can be coordinated, which can be managed in the cloud platform of the service management module 240. Commands are issued in the interface to realize remote operation.
  • the cloud computing terminal 200 can realize functions such as real-time monitoring and remote management, reduce labor consumption and improve system efficiency.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Power Engineering (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)

Abstract

Système informatique nuage-périphérie pour un véhicule électrique pur, comprenant une extrémité informatique en nuage (200) et au moins deux extrémités en périphérie (100). Les extrémités en périphérie (100) sont utilisées pour obtenir des informations de véhicule et prétraiter les informations de véhicule afin de générer des informations physiques multi-domaines; l'extrémité informatique en nuage (200) est connectée aux extrémités en périphérie (100), utilisée pour commander chaque extrémité en périphérie (100), et utilisée en outre pour effectuer une fusion et une gestion sur les informations physiques multi-domaines. Afin d'assurer un fonctionnement stable d'un véhicule électrique, les extrémités en périphérie (100) sont appliquées afin de surveiller le véhicule électrique à partir de trois positions, à savoir, un état de mouvement de véhicule, une batterie de véhicule et un moteur de véhicule, différents capteurs (111, 121, 131, 141) étant fournis afin de générer des informations redondantes, ce qui permet d'augmenter le degré de précision de surveillance. Deux couches de structures de traitement d'informations sont fournies, des ressources informatiques des extrémités en périphérie (100) sont régulées par application de l'extrémité informatique en nuage (200), et les informations physiques multi-domaines sont fusionnées et gérées, ce qui permet de mieux contrôler les informations globales et d'assurer la stabilité du système global.
PCT/CN2020/122406 2020-07-08 2020-10-21 Système informatique nuage-périphérie pour véhicule électrique pur WO2022007235A1 (fr)

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CN202021328583.8U CN213007637U (zh) 2020-07-08 2020-07-08 一种纯电动汽车的边-云计算系统
CN202021328583.8 2020-07-08

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WO2018057532A1 (fr) * 2016-09-23 2018-03-29 Cougeller Research Llc Modélisation de transfert de charge de batterie comprenant une mesure de tension et de courant à réponse de filtre alignée temporellement
CN110083099A (zh) * 2019-05-05 2019-08-02 中国汽车工程研究院股份有限公司 一种符合汽车功能安全标准自动驾驶架构系统和工作方法
JP2020046333A (ja) * 2018-09-20 2020-03-26 株式会社ケーヒン バッテリ監視装置

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20150000280A (ko) * 2013-06-24 2015-01-02 제주대학교 산학협력단 D2d 통신 기반의 모바일 단말을 이용한 전기 자동차 상태 관리 및 제어 시스템
CN103763381A (zh) * 2014-01-27 2014-04-30 河南速达电动汽车科技有限公司 一种电动汽车动力电池远程监测装置
CN105620467A (zh) * 2014-10-31 2016-06-01 比亚迪股份有限公司 混合动力车辆及混合动力车辆的驱动控制方法
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CN110083099A (zh) * 2019-05-05 2019-08-02 中国汽车工程研究院股份有限公司 一种符合汽车功能安全标准自动驾驶架构系统和工作方法

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