Figure 5 - available via license: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported
Content may be subject to copyright.
Source publication
To develop competitive vehicles with ever increasing complexity, automotive designers need to improve their ability to explore a broad range of system architectures efficiently and effectively. Whereas traditional vehicle systems are based on internal combustion (IC) engines, today's environmentally conscious vehicle manufacturers must consider alt...
Context in source publication
Context 1
... logical subsystem, except for the Vehicle Systems Control, is further decomposed into a physical Plant and a Controls part, as is shown in Figure 5. The interface between the Plant and the Controller consists of the sensor signals flowing from the Plant to the Controller, and the actuator signals flowing from the Controller to the Plant. ...
Similar publications
This paper shows the modeling and simulation of fuel economy and vehicle dynamics of a heavy truck with Modelica. The work was carried out on MWorks, which is developed by Huazhong Univer-sity of Science & Technology. Comparisons be-tween measured data and simulation results va-lidate the correctness of the model, and demon-strate that Modelica can...
The objective of this work consists on presenting a simulation model developed to study the transient operation of a solar aided biomass steam generator integrated into an existing cogeneration plant installed in Brazil. The proposed side-by-side hybridization concept when operated under the fuel economy mode turns possible to reduce the fuel consu...
Citations
... Several researchers have addressed key challenges in modeling and simulation by establishing template-based approaches. For example Branscomb and colleagues [22] establish the Vehicle Architecture Modeling Frameworks (VAMF) based on SysML and the Vehicle Model Architecture (VMA) to address challenges with integrating multi-disciplinary simulation and analysis models. The VMA is developed to support model-based system engineering of vehicles with a focus on differing levels of decomposition and fidelity. ...
... In this approach, system engineers first build a reference architecture model which acts as a central starting point for the development of a product line. The reference architecture formally defines the key subsystems of the product line and maps the interactions between them [25]. The system architect also works with stakeholders to decide which features the product line will provide, and he maps these features onto a feature model [26]. ...
... Alternatively, other work has developed a framework for using a reference architecture model in SysML to manage the block interfaces and signal flow in the Simulink model [25] [44]. While this framework effectively uses SysML to manage variants-even architectural variants-in Simulink, much of the modeling effort must still be accomplished manually. ...
Current workflows for creating simulations of ground vehicle systems are non-standardized and full of bottlenecks and inefficient point-to-point communication. This paper proposes the use of a SysML reference architecture to act as the single source of information for system-level simulation creation. SysML is already used to create reference architectures for system design, but extending it to the simulation domain will require special considerations, including how to represent models at different levels of fidelity, how to have an implementation-independent view of control algorithms, and how to link simulation artifacts to their description model counterparts. This paper details the additional challenges of managing simulations, defines a new simulation perspective for a SysML reference architecture, describes methods for mapping between the simulation and physical perspectives, and discusses the organization of a reference architecture for ground vehicle simulations. The benefits of using a SysML reference architecture for system-level simulation management include having a dynamic and centralized representation of existing simulation components, a standardized architecture to facilitate the creation of new simulations, and streamlined communication with all teams involved in creating simulations, reducing the overall cost of generating system-level simulations of ground vehicles.
... The paper shows how to leverage genetic algorithms in an existing MBPLE to perform a deeper trade study analysis at the component level to address the concerns about performance (i.e., output power and speed) and physical (i.e., mass) requirements. The contribution is expected to help systems engineers reduce the human efforts to perform traditional (brute-force) trade studies which are timeconsuming [15] and error-prone [16]. Figure 1 shows the 150%-logical architecture model used in this paper, which is illustrated in a block definition diagram (BDD). ...
... To conduct a trade study, system engineers usually need to design a number of alternatives 100%-logical-architecture model of a system and manually analyze them to find the best design for component level [23] [26]. This process is often time and cost consuming [15] and error-prone [16]. The complexity of systems created two issues in component selection [18] [27]: (1) The problem in performing an extensive search to discover the component combination(s) through many possibilities; and (2) The problem that occurs when there is no feasible combination exists to satisfy the requirements. ...
... There are a vast amount of researches that show the effectiveness of using SysML for designing vehicular control systems. Utilization of SysML in modeling control systems of autonomous vehicles is one example that clearly shows the benefits of applying MBSE to system development in automotive industry [3,4,5,6,7]. ...
Vehicular control systems are characterized with
numerous complex interactions with a steady rise of
autonomous functions, which makes it more challenging for designers and safety engineers to identify unexpected failures. These systems tend to be highly integrated
and exhibit features like concurrency for which traditional
verification and validation techniques (i.e. testing and simulation) are insufficient to provide rigorous and complete assessment. Model Checking, a well-known formal verification
technique, can be used to rigorously prove the correctness of
such systems according to design Requirements. In particular,
Model Checking is a method for formally verifying finite-state
concurrent systems. Specifications about the system are
expressed as temporal logic formulas, and efficient symbolic
algorithms are used to traverse the model defined by the
system and check if the specification holds or not. Systems
Modeling Language (SysML) has been widely used in architectural and functional modeling in automotive industries.
However, it cannot directly be verified against safety requirements. In this work, SysML is used to establish a unified
system model that can present an integrated autonomy
software and hardware system of a vehicular control system.
A generic model transformation strategy is developed to integrate SysML with one of the state-of-the-art Model Checking
tools, NuSMV. Cameo Systems Modeler is an industry leading
cross-platform collaborative Model-Based Systems
Engineering environment for designing standard-compliant
SysML models and diagrams. A native Cameo's plugin is
constructed to transform SysML state machines to the input
language of NuSMV model checker and also to replay the
verification results back into the Cameo's environment. A case
study of an executable state machine for a high-level autonomous driving system is built. The NuSMV model checker is
used to model check the state machine of the autonomous
driving system against design requirements expressed as
temporal logic formulas. Upon violation of design requirements, our SysML-NuSMV integration allows to replay counterexamples in the Cameo modeling environment. Thus a
bi-directional integration of system modeling language with
the model checker is developed and the transformation rules
are defined. The case study result shows how this method can
help designers and safety engineers to automatically identify
hidden design errors in a variety of possible design models.
... Due to the increasing system complexity, architects have to choose among a combinatorially growing number of design options: exploring architectural design spaces, and bringing the best alternatives out of the solution space has often become beyond human capacity [12]. The need for automated design space exploration that improves an existing architecture specification has been recognized [2,5,16,24,26], but searching through a large number of possibilities is often time-and cost-consuming [9], and error-prone [6]. ...
Exploring architectural design space is often beyond human capacity and makes architectural design a difficult task. Model-based systems engineering must include assistance to the system designer in identifying candidate architectures to subsequently analyze trade-offs. Unfortunately, existing languages and approaches do not incorporate this concern, generally favoring solution analysis over exploring a set of candidate architectures. In this paper, we explore the advantages of designing and configuring the variability problem to solve one of the problems of exploring (synthesizing) candidate architectures in systems engineering: the resource allocation problem. More specifically, this work reports on the use of the Clafer modeling language and its gateway to the CSP Choco Solver, on an industrial case study of heterogeneous hardware resource allocation (GPP-GPGPU-FPGA). Based on experiments on the modeling in Clafer, and the impact of its translation into the constraint programming paradigm (per-formance studies), discussions highlight some issues concerning facilities for modeling and synthesis of architectures and recommendations are proposed towards the use of this variability approach.
... Meanwhile, the complexity of the systems complicates the process to drag out the best alternatives from the solution space. Searching through a large number of possibilities is often time-and cost-consuming (Dinger 1998), and error-prone (Branscomb et al. 2013). Thus, an optimization of the searching method is needed to overcome this issue (Dinger 1998). ...
Component‐Selection is an important task in design synthesis of MBSE. A trade study is commonly used to help systems engineers and stakeholders selecting the components of a systems design. A simple analysis may be sufficient when it involves only two parameters. However, when the components and their integration become more complex, the trade study also becomes harder, time‐ and cost‐consuming, and error‐prone. This paper aims to propose a method to automatically generate the solution by performing an evolutionary search. Sample components of a hybrid car which consists of an engine, an electric motor, and a battery are used in our initial prototype. The logical architecture is represented in the OMG SysMLTM via CSMTM. Through the experimental result, this paper shows that the proposed technique allowed the system design to be efficiently selected.
... It is worth mentioning that SysML can be used to model systems based on various paradigms, such as procedural, object-oriented, and component-based [17]. Another advantage is still growing popularity of SysML and its application in various engineering domains [18][19][20]. ...
... The effect of the uncertainties in one domain model may propagate to another through interrelated variables, and the system output finally suffers from the accumulated effect of the individual uncertainties. Thus, the information flow in modeling practice is one of the key aspects of its uncertainty, which may imply risk that the product attributes does not ultimately meet user needs [2]. ...
... Focusing on the companies' organizational level, the vehicle partitions affect also the tasks, roles and simulation models delegation between related engineering disciplines. The complex, multidisciplinary (or multi-domain) simulation model creation process involves a number of parallel or/and sequential activities in which experts in different domains, possibly in different companies (i.e., suppliers and sub-tier suppliers) create, reuse and exchange domain (or component or atomic) level models to build up a full-vehicle system model [2]. Each engineering discipline tends to use its own domain-specific languages, tools and methods to model different aspects of a system concurrently. ...
... Architectures provide a holistic view of a system and allow different stakeholders to work together with a common basis in the same vehicle system definition [12]. To design a good vehicle, it is necessary to analyze each of these system architectures from a variety of perspectives including performance, fuel economy, or even thermal behavior [2,13]. Creating all possible system architectures manually is necessary for the first time but the reuse of an existing architecture is recommended because of time and cost concerns. ...
Today, one of the major challenges in full-vehicle model creation is to get domain models from different experts while detecting any potential inconsistency problem before the IVVQ (Integration, Verification, Validation, and Qualification) phase. To overcome such challenges, Conceptual Design phase has been adapted to the current Model Development Process (MDP). For that, the system engineer starts to define the most relevant model architecture by respecting quality and time constraints. Next, the architect model designs the delivered model architecture in a more formal way to support the integration of domain models in a consistent fashion. Finally, the architect model negotiates with different model providers with the aim of
specifying vehicle and domain level models and their interfaces connections. To improve knowledge sharing between mentioned actors, we propose a Model Identity Card (MIC) for classifying analysis modeling knowledge including input/output parameters and accuracy expectation. The fundamental concepts that form
the basis of all engineering analysis models are identified and typed for implementation into a computational environment. An industrial case study of engine-after treatment model is used to show how MICs and integrated model design phase might use in a given scenario. A validation protocol is conducted through a
heuristic observation to estimate the rate of model rework and ambiguity reduction.
... Kim et al. 23 integrated the SysML models with analysis models, thereby enabling designers to quickly evaluate system configurations by executing the analysis models. Branscomb et al. 24 developed a vehicle architecture modeling framework (VAMF), which combined SysML, Modelica and Simulink models in a systematic process to generate a fully integrated vehicle-level attribute analysis model. Similar studies have been conducted by other researchers. ...
... The above analysis indicates that many studies attempt to use SysML-based model integration to generate different types of models, for example, the analysis model, [23][24][25] the simulation model 7,26,27 and the control model, 8 from the SysML models. However, the integration of SysML models with CAD models has received little attention. ...
The system-level structure model significantly affects the subsequent development process. However, such a model cannot be used directly due to its document-based representation. A significant gap exists between the system-level model and the detailed domain-specific model. The model integration method significantly facilitates the design scenario involving different design phases because it supports tasks such as complexity management and consistency maintenance. However, the automated generation of the computer-aided design model from the systems modeling language-based structure model of the mechanical system is a typical issue. In this study, a meta-model-based approach is proposed to generate the initial computer-aided design model represented by the STEP file from the systems modeling language-based system structure model. A geometry-related system structure modeling method is described, and the triple graph grammar is introduced to transform the systems modeling language model into the EXPRESS model. An automated generation algorithm is proposed to construct the initial computer-aided design model for mechanical systems against the ISO 10303-203 (AP 203) standard by parsing the EXPRESS model. Our approach facilitates model integration and helps reduce the gap between the system-level structure model and the computer-aided design model. This reduction would be beneficial for eliminating misunderstandings between different designers and thus to accelerate the design process. Finally, an example of an engine is provided to illustrate the proposed method.
... Focusing on the companies' organizational level, the vehicle partitions affect also the tasks, roles and simulation models delegation between related engineering disciplines. The complex, multidisciplinary (or multi-domain) simulation model creation process involves a number of parallel or/and sequential activities in which experts in different domains, possibly in different companies (i.e., suppliers and sub-tier suppliers) create, reuse and exchange domain (or component or atomic) level simulation models to build up a full-vehicle system model [2]. Each engineering discipline tends to use its own domainspecific languages, tools and methods to model different aspects of a system concurrently. ...
... Distributed design teams typically handle the model at different levels of abstraction, ranging from very high-level system decompositions to very low-level detailed specification of components [3]. This is particularly challenging for the design of multidisciplinary systems in which components in different disciplines (e.g., mechanics, structural dynamics, hydrodynamics, heat conduction, fluid flow, transport, chemistry, or acoustics) are tightly coupled to achieve optimal system performance [2]. In this multidisciplinary collaborative design environment, most of the engineers modify the existing simulation models to fulfill a specific purpose for which they were not originally made; it can be a source of inaccuracy, uncertainty, duplication and time delay. ...
... The effect of the uncertainties in one domain model may propagate to another through interrelated variables, and the system output finally suffers from the accumulated effect of the individual uncertainties. Thus, the information flow in modeling practice is one of the key aspects of its uncertainty, which may imply risk that the product attributes does not ultimately meet user needs [2]. ...
Today, one of the major challenges in full-vehicle model creation is to get domain models from different experts while detecting any potential inconsistency problem before the IVVQ (Integration, Verification, Validation, and Qualification) phase. To overcome such challenges, Conceptual Design phase has been adapted to the current Model Development Process (MDP). For that, the system engineer starts to define the most relevant model architecture by respecting quality and time constraints. Next, the model architect designs the delivered model architecture in a more formal way to support the integration of domain models in a consistent fashion. Finally, the model architect negotiates with different model providers with the aim of specifying vehicle and domain level models and their interfaces connections. To improve knowledge sharing between mentioned actors, we propose a Model Identity Card (MIC) for classifying analysis modeling knowledge including input/output parameters and quality expectation. The fundamental concepts that form the basis of all simulation models are identified and typed for implementation into a computational environment. An industrial case study of engine-after treatment model is used to show how MICs and integrated model design phase might use in a given scenario. A validation protocol is conducted through a heuristic observation to estimate the rate of model rework and ambiguity reduction.
