基于MBSE的智能汽车信息物理系统建模方法.pdf
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1、汽 车 文 摘徐天啸梁浩赵静高小栋闫涵(国汽(北京)智能网联汽车研究院有限公司,北京 100176)【摘要】智能车辆信息物理系统(IVCPS)可以基于道路和车辆信息资源实时控制车辆的运行轨迹,在降低车辆能耗方面具有很大潜力。然而,目前对基于云的预测巡航控制(CPCC)体系结构的研究忽略了体系结构实现和应用的可行性,没有对体系结构的合理性进行验证。为建立IVCPS体系结构与应用验证之间的联系,促进IVCPS多领域、多学科协同设计、联合仿真、系统集成,提出了基于模型系统工程(MBSE)的IVCPS建模方法。首先,构建了IVCPS的整体分层体系结构,明确了各层体系结构的构成要素。然后选择系统建模语言
2、(SysML)作为建模工具,构建了需求-功能-逻辑-参数(RFLP)建模框架。最后,以IVCPS云预测巡航控制系统为例,利用RFLP框架对CPCC系统的需求、功能、逻辑和参数进行建模和分析。模拟结果证明MBSE可以实现对CPCC系统的需求分析、功能分解、逻辑架构设计和系统参数标定进行统一建模,促进CPCC系统理论架构的仿真验证,并能够测试、分析CPCC架构对于智能网联汽车的运行轨迹优化和油耗降低效果。本研究旨在为提高IVCPS系统建模的交互性、可重用性和兼容性奠定基础。关键词:基于模型系统工程;智能车辆信息物理系统;系统建模语言;基于云的预测巡航控制中图分类号:U462.1文献标识码:ADOI
3、:10.19822/ki.1671-6329.20230202基于MBSE的智能汽车信息物理系统建模方法*【欢迎引用】徐天啸,梁浩,赵静,等 基于MBSE的智能汽车信息物理系统建模方法J.汽车文摘,2023(10):1-16.Modeling Method for Intelligent Vehicle Cyber-Physical System Basedon MBSE*Xu Tianxiao,Liang Hao,Zhao Jing,Gao Xiaodong,Yan Han(China Intelligent and Connected Vehicles(Beijing)Research I
4、nstitute Co.,Ltd.,Beijing 100176)【Cite this paper】XU T X,LIANG H,ZHAO J,et al.Modeling Method for Intelligent Vehicle Cyber-Physical System Based on MBSEJ.Automotive Digest(Chinese),2023(10):1-16.【Abstract】The Intelligent Vehicle Cyber-Physical System(IVCPS)can control the operation trajectory of ve
5、hiclesbased on road and vehicle information resources in real time,which has great potential in reducing vehicle energyconsumption.However,the current studies on Cloud-Based Predictive Cruise Control(CPCC)architecture ignore thefeasibility of architecture implementation and application,without verif
6、ing the rationality of the architecture.To establishthe links among architecture,application and verification,promote multi-domain and multi-disciplinary collaborativedesign,joint simulation as well as system integration in IVCPS,this paper proposes the modeling method of IVCPS basedon Model-Based S
7、ystems Engineering(MBSE).Firstly,the overall layered architecture of IVCPS is constructed and theelements of each layer of the architecture are clarified.Then Systems Modeling Language(SysML)is utilized as themodeling tool and the Requirement analysis-Functional analysis-Logical analysis-Parametric
8、calibration(RFLP)modelingframework is constructed.Finally,a typical scenario of CPCC system within IVCPS is taken as an example.The RFLPframework is utilized to model and analyze the requirements,functions,logics and parametric calibration of the CPCCsystem.The modeling results prove that MBSE can r
9、ealize the unified modeling of the requirement analysis,functiondecomposition,logical architecture design and system parameter calibration of the CPCC system,promote simulationverification of the theoretical architecture of the CPCC system and be able to test and analyze the effectiveness of the CPC
10、Carchitecture in optimizing the running trajectory and reducing fuel consumption of intelligent connected vehicles.This studylays a foundation for improving the interactivity,reusability and compatibility of IVCPS system modeling.Key words:Model-based Systems Engineering,Intelligent Vehicle Cyber-Ph
11、ysical System,System Modeling Language,Cloud-based Predictive Cruise Control*Funding Project:National Key R&D Program of China(Grant No.2021YFB2501000)2023年中国汽车工程学会年会优秀论文(选登)Automotive Digest12023年 第10期AbbreviationsCPSCyber-Physical SystemICVIntelligent and Connected VehicleIVCPSIntelligent Vehicle
12、Cyber-Physical SystemCCSCloud-based Control SystemTBSEText-Based Systems EngineeringMBSEModel-Based Systems EngineeringSysMLSystems Modeling LanguageRFLPRequirement analysis-Functional analysis-Logical analysis-Parametric calibrationCPCCCloud-Based Predictive Cruise Control0IntroductionUnder the rap
13、id development of information technologies,vehicles are developing in the direction of intelligence and connecting,the application of Cyber-PhysicalSystem(CPS)in the Intelligent and Connected Vehicle(ICV)field becomes an important research topic1-2.Intelligent Vehicle Cyber-Physical System(IVCPS)obt
14、ainsreal-time information of roads,traffic and vehicles fromthe Cloud-based Control System(CCS),uses the computing ability of the cloud to quickly calculate the drivingstrategy of the car and transmit it to the ICV.This controlmode can significantly improve the safety of vehicle driving and reduce e
15、nergy consumption,which is of great significance for the development of vehicles in the directionof low carbon and energy saving3-4.At present,research on CPS,ICV and CCS focuses on network architecture and control algorithms.Xiaet al.5designed an intelligent transportation networkphysical control s
16、ystem based on CCS,the simulation results show that the system improves the dynamic performance of the traffic control system.Based on CPS theory,Li et al.2proposed CCS architecture for ICVs,which iscommitted to connecting the 2 main fields of intelligenttransportation system and ICV,aiming to accel
17、erate thedevelopment of ICV.For control algorithms,Li et al.6solved the optimal speed using accurate vehicle and fuelconsumption models on a cloud computing platform anddeveloped field experiments.Li et al.7performed predictive cruise control for heavy duty commercial vehicles onthe highway by predi
18、cting slope information.Gao et al.8considered the influence of intersection queuing lengthand dissipation time on vehicle driving,proposed a queuing dissipation time estimation model,which saves busenergy consumption and reduces waiting time.The abovestudies have achieved many good results.However,t
19、heresearch on architecture is often only theoretical from theperspective of requirements,it ignores the feasibility ofapplication,the research on models and algorithms oftenneeds to first determine the fixed architecture and specific scenarios,when the elements of the architecture orscene change,the
20、 model and algorithm need to be adjusted.Therefore,it is necessary to realize the collaborativedesign,joint simulation and system integration of IVCPS,so that the requirements,architecture,model,algorithmand application of IVCPS are coordinated,the compatibility and reusability of the architecture a
21、re improved.Systems engineering-based methods can solve modelingproblems of such multi-domain,multi-disciplinary complex systems.Thetraditionalsystemengineeringfieldusesthe Text-Based Systems Engineering(TBSE)method9-10,which realizes the task assignment,information interaction between departments a
22、nd information exchangeamong different disciplines through a series of documents,tables,drawings and diagrams,such as operationdocuments,specifications,interface definition documentsand architecture specifications.However,TBSE has thedisadvantages of poor requirements traceability,insufficient reuse
23、 and scalability.In recent years,MBSE11-13isproposed to address these disadvantages and graduallybecomes a popular method in the field of systems engineering modeling.MBSE uses the model to express therequirements,design,analysis and verification process ofa system in the whole life cycle.MBSE can r
24、ealize thedigital and graphical expression of the system throughthe model so as to improve the efficiency of system design.Many research institutions have explored the application of MBSE theory in various industries,differentmodeling languages,tools and processes are proposed,such as Harmony SE met
25、hod14,object-oriented systemsengineering method15as well as Magic-grid method16,et al.These studies are applied mainly in the fields ofaerospace17,nuclear energy18and automated factories19.汽车文摘2汽 车 文 摘There is no public research in fields of ICV and CPS.To address the engineering modeling issue of c
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- 基于 MBSE 智能 汽车信息 物理 系统 建模 方法
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