1,625 research outputs found

    Co-Simulation Methods for Holistic Vehicle Design: A Comparison

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    Vehicle development involves the design and integration of subsystems of different domains to meet performance, efficiency, and emissions targets set during the initial developmental stages. Before a physical prototype of a vehicle or vehicle powertrain is tested, engineers build and test virtual prototypes of the design(s) on multiple stages throughout the development cycle. In addition, controllers and physical prototypes of subsystems are tested under simulated signals before a physical prototype of the vehicle is available. Different departments within an automotive company tend to use different modelling and simulation tools specific to the needs of their specific engineering discipline. While this makes sense considering the development of the said system, subsystem, or component, modern holistic vehicle engineering requires the constituent parts to operate in synergy with one-another in order to ensure vehicle-level optimal performance. Due to the above, integrated simulation of the models developed in different environments is necessary. While a large volume of existing co-simulation related publications aimed towards engineering software developers, user-oriented publications on the characteristics of integration methods are very limited. This paper reviews the current trends in model integration methods applied within the automotive industry. The reviewed model integration methods are evaluated and compared with respect to an array of criteria such as required workflow, software requirements, numerical results, and simulation speed by means of setting up and carrying out simulations on a set of different model integration case studies. The results of this evaluation constitute a comparative analysis of the suitability of each integration method for different automotive design applications. This comparison is aimed towards the end-users of simulation tools, who in the process of setting up a holistic high-level vehicle model, may have to select the most suitable among an array of available model integration techniques, given the application and the set of selection criteria

    Modelling and Co-simulation of hybrid vehicles: A thermal management perspective

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    Thermal management plays a vital role in the modern vehicle design and delivery. It enables the thermal analysis and optimisation of energy distribution to improve performance, increase efficiency and reduce emissions. Due to the complexity of the overall vehicle system, it is necessary to use a combination of simulation tools. Therefore, the co-simulation is at the centre of the design and analysis of electric, hybrid vehicles. For a holistic vehicle simulation to be realized, the simulation environment must support many physical domains. In this paper, a wide variety of system designs for modelling vehicle thermal performance are reviewed, providing an overview of necessary considerations for developing a cost-effective tool to evaluate fuel consumption and emissions across dynamic drive-cycles and under a range of weather conditions. The virtual models reviewed in this paper provide tools for component-level, system-level and control design, analysis, and optimisation. This paper concerns the latest techniques for an overall vehicle model development and software integration of multi-domain subsystems from a thermal management view and discusses the challenges presented for future studies

    Co-Simulation in Virtual Verification of Vehicles with Mechatronic Systems

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    In virtual verification of vehicle and mechatronic systems, a mixture of subsystems are integrated numerically in an offline simulation or integrated physically in a hardware-in-loop (HIL) simulation. This heterogeneous engineering approach is crucial for system-level development and widely spreads with\ua0the industrial standard, e.g. Functional Mock-Up Interface (FMI) standard.For the engineers, not only the local subsystem and solver should be known,\ua0but also the global coupled dynamic system and its coupling effect need to be\ua0understood. Both the local and global factors influence the stability, accuracy, numerical efficiency and further on the real-time simulation capability.In this thesis, the explicit parallel co-simulation, which is the most common and closest to the integration with a physical system, is investigated.In the vehicle development, the vehicle and the mechatronic system, e.g. an\ua0Electrcial Power Assisted Steering (EPAS) system can be simulated moreefficiently by a tailored solver and communicative step. The accuracy and\ua0numerical stability problem, which highly depends on the interface dynamics, can be investigated similarly in the linear robust control framework. The\ua0vehicle-mechatronic system should be coupled to give a smaller loop gain for robustness and stability. Physically, it indicates that the splitting part\ua0should be less stiff and the force or torque variable should be applied towardsthe part with a higher impedance in the force-displacement coupling. Furthermore, to compensate the troublesome low-passed and delay effect fromthe coupling, a new coupling method based on H∞ synthesis is developed,\ua0which can improve the accuracy of co-simulation. The method shows robustness to the system dynamics, which makes it more applicable for a complex\ua0vehicle-mechatronic system

    The Internet of Simulation: Enabling Agile Model Based Systems Engineering for Cyber-Physical Systems

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    The expansion of the Internet of Things (IoT) has resulted in a complex cyber-physical system of systems that is continually evolving. With ever more complex systems being developed and changed there has been an increasing reliance on simulation as a vital part of the design process. There is also a growing need for simulation integration and co-simulation in order to analyse the complex interactions between system components. To this end we propose that the Internet of Simulation (IoS) as an extension of IoT can be used to meet these needs. The IoS allows for multiple heterogeneous simulations to be integrated together for co-simulation. It's effect on the engineer process is to facilitate agile practices without sacrificing rigour. An Industry 4.0 example case study is provided showing how IoS could be utilized

    Co-Simulation of Cyber-Physical System with Distributed Embedded Control

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    Future Perspectives of Co-Simulation in the Smart Grid Domain

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    The recent attention towards research and development in cyber-physical energy systems has introduced the necessity of emerging multi-domain co-simulation tools. Different educational, research and industrial efforts have been set to tackle the co-simulation topic from several perspectives. The majority of previous works has addressed the standardization of models and interfaces for data exchange, automation of simulation, as well as improving performance and accuracy of co-simulation setups. Furthermore, the domains of interest so far have involved communication, control, markets and the environment in addition to physical energy systems. However, the current characteristics and state of co-simulation testbeds need to be re-evaluated for future research demands. These demands vary from new domains of interest, such as human and social behavior models, to new applications of co-simulation, such as holistic prognosis and system planning. This paper aims to formulate these research demands that can then be used as a road map and guideline for future development of co-simulation in cyber-physical energy systems

    Virtual prototyping of vehicular electric steering assistance system using co-simulations

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    Virtual prototyping is a practical necessity in vehicle system development. From desktop simulation to track testing, several simulation approaches, such as co-simulation and hardware-in-loop (HIL) simulation, are used. However, due to interfacing problems, the consistency of testing results may not be ensured. Correspondingly, inherent inaccuracies result from numerical coupling error and non-transparent HIL interface, which involves control tracking error, delay error, and attached hardware and noise effects. This work aims to resolve these problems and provide seamless virtual prototypes for vehicle and electric power-assisted steering (EPAS) system development.The accuracy and stability of explicit parallel co-simulation and HIL simulation are investigated. The imperfect factors propagate in the simulation tools like perturbations, yield inaccuracy, and even instability according to system dynamics. Hence, reducing perturbations (coupling problem) and improving system robustness (architecture problem) are considered.In the coupling problem, a delay compensation method relying on adaptive filters is developed for real-time simulation. A novel co-simulation coupling method on H-infinity synthesis is developed to improve accuracy for a wide frequency range and achieve low computational cost. In the architecture problem, a force(torque)-velocity coupling approach is employed. The application of a force (torque) variable to a component with considerable impedance, e.g., the steering rack (EPAS motor), yields a small loop gain as well as robust co-simulation and HIL simulation. On a given EPAS HIL system, an interface algorithm is developed for virtually shifting the impedance, thus enhancing system robustness.The theoretical findings and formulated methods are tested on generic benchmarks and implemented on a vehicle-EPAS engineering case. In addition to the acceleration of simulation speed, accuracy and robustness are also improved. Consequently, consistent testing results and extended validated ranges of virtual prototypes are obtained

    CAE - PROCESS AND NETWORK : A methodology for continuous product validation process based on network of various digital simulation methods

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    CAE ProNet methodology is to develop CAE network considering interdependencies among digital validations. Utilizing CAE network and considering industrial requirements, an algorithm is applied to execute a product, vehicle development phase, and load case priority oriented CAE process. Major advantage of this research work is to improve quality of simulation results, reducing time-to-market and decreasing dependencies on hardware prototype
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