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Collaborative robots are growing exponentially, with applications in the most diverse domains and operating side by side with humans in unstructured and changing environments. Such a scenario requires robot programmers to develop complex applications, integrating Artificial Intelligence (AI), sensing and control, both rapidly and efficiently. Python and model-based design software packages such as Simulink are widely used in engineering, and when it comes to robotics those tools are very important for robot design, simulation and the development of control algorithms before the implementation on the real robot. Python is widely used in AI while Simulink supports several hardware components, facilitating rapid deployment of the developed programs on the target hardware. In this study, a novel Python library (iiwaPy) and SimulinkIIWA are presented to interface KUKA iiwa robots. The iiwaPy is based on the Transmission Control Protocol/Internet Protocol (TCP/IP) and the SimulinkIIWA on the User Datagram Protocol (UDP). Both support robot motion control (point-to-point and real-time) at the joint level and the end-effector (EEF) level, as well as the monitoring of the robot state (position, orientation, torques feedback). Open-source code and example applications are provided showing the flexibility and the ease of use of the proposed interfaces. [ABSTRACT FROM AUTHOR]

In many fields including aerospace, automotive, and telecommunications, MathWorks' MATLAB/Simulink is contemporary standard for model-based design. The strengths of Simulink are rapid design and algorithm exploration. Models created with Simulink are just functional. Therefore, designers cannot effortlessly consider a Simulink model's architecture. As current architectures are optimized to run on multicore processors, software running on these processors needs to be parallelized in order to benefit from their natural performance. For instance, designers need to understand how a Simulink model could be parallelized and how an adequate multicore architecture is selected. This paper focuses on the dataflow-based parallelization of Simulink models and proposes a method based on dataflow to measure the performance of parallelized Simulink models running on multicore architectures. Throughout the parallelization process, the model is converted into a Hierarchical Synchronous DataFlow Graph (HSDFG) keeping its original semantics, and each composite node in the graph is flattened. Then, the graph is mapped and scheduled into a multicore architecture with the ultimate objective that minimizes the end-to-end latency. In the experiment of applying the proposed approach to a real Simulink model, latency of the parallelized model could be reduced successfully on a various multi-core architectures. [ABSTRACT FROM AUTHOR]

The development of electric gerotor pumps is a complex multiphysical optimization problem. To develop optimal systems, accurate simulation models are required to increase digital reliability. An important challenge is the accurate prediction of the pump behavior for extreme temperatures in automotive applications from − 40 °C to 110 °C, where the viscosity of the fluid changes significantly. Therefore, simulation-based methods (numerical methods for calculating viscous friction) were developed and validated by measurements, including climatic chamber tests. The results show a strong correlation between simulated and measured performance characteristics, especially in terms of volumetric flow rate ( < 5 % ), pump torque and efficiency ( < 7 % ) at different temperature and viscosity conditions over a wide speed range (1000–5000 rpm) and different system pressures (0.5–5 bar). A novel method for simulating the cold start behavior of pumps (journal bearing approach for outer gear in pump housing) was introduced and validated by measurements. The methods presented significantly reduce the need for physical testing and accelerate the development process, as the pump behavior at each operating point can be accurately predicted before a hardware prototype is built. This improves the understanding of gerotor pump characteristics and provides insights to further improve the model-based development of electric oil pumps for the automotive industry. [ABSTRACT FROM AUTHOR]

This study introduces a robust model-based framework designed for the verification and validation (V&V) of Attitude Determination and Control Systems (ADCSs) in nanosatellites, focusing on magnetic actuation while still being applicable to larger spacecraft platforms. By employing Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), Processor-in-the-Loop (PIL), and Hardware-in-the-Loop (HIL) methodologies, this framework enables a thorough and systematic approach to testing and validation. The framework facilitates the assessment of long-term maneuvers, addressing challenges such as initial small-attitude errors and restricted 3D movements. Two specific maneuvers are evaluated: detumbling and nadir pointing, utilizing quaternions and a comprehensive suite of sensors, including six sun sensors, a three-axis magnetometer, a three-axis gyroscope, GPS, and three magnetorquers. The methodologies—MIL, SIL, PIL, and HIL—integrate the behaviors of digital sensors, analog signals, and astrodynamic perturbations. Based on an optimized SIL environment, Monte Carlo simulations were performed to optimize control gains for nadir pointing, achieving a mean pointing accuracy of 11.69° (MIL) and 18.22° (PIL), and an angular velocity norm of 0.0022 rad/s for detumbling. The HIL environment demonstrated a mean pointing accuracy of 9.96° and an angular velocity norm of 0.0024 rad/s. This comprehensive framework significantly advances the design and verification processes for nanosatellite ADCSs, enhancing the reliability and performance of nanosatellite missions. [ABSTRACT FROM AUTHOR]

During an engineering design process, designers create sequences of product models by switching between product models with different purposes. To enable an efficient use of these product models, researchers are required to anticipate the compatibility of the models in application by designers. This is necessary as the information in an existing product model may not be usable for a subsequent product model. However, the corresponding information on compatibility was not accessible to researchers as it was scattered across various publications. Hence, the objective of this contribution was to develop a structured overview, a landscape of linkable and non-linkable product models in embodiment design to merge the information. For this purpose, a literature review containing a grounded theory-based analysis was conducted and the results were visualized using the network visualization software Gephi. The key learnings of the visualized landscape of 52 product models can be summarized as follows: (1) some models are already closely linked to each other by compatible inputs and outputs; (2) other product models are noticeable with mostly unknown linking possibilities due to incompatible inputs and outputs or insufficient descriptions in the literature. 14 product models offer two linking possibilities or less. In these cases, it is unclear how they interact with other product models in an engineering design process. In conclusion, the product model landscape provides insight into the compatibility of product models to support the development of existing and new product models for sequential use by designers. [ABSTRACT FROM AUTHOR]

In this paper, we address the issue of whether to optimize or satisfice in model-based engineering design. When dealing with operations research problems in the context of engineering design, one may encounter (i) nonlinear, nonconvex objectives and constraints, (ii) objectives with different units, and (iii) computational models that are abstractions of reality and fidelity, Seeking a single-point optimal solution that meets the necessary and sufficient Karush–Kuhn–Tucker (KKT) conditions makes it impossible to obtain a solution that satisfies all the targeted goals. Instead, a method to identify satisficing solutions that satisfies necessary KKT condition but not the sufficient condition is proposed. These solutions are relatively robust, easy to acquire, and often good enough. In this paper, we demonstrate the combined use of the compromise Decision Support Problems and the adaptive linear programming algorithm, as proposed by Mistree and co-authors. This method is appropriate in formulating design problems and obtaining solutions that satisfy only the necessary KKT condition. Further, the use of the proposed method circumvents complications associated with the use of gradient-based optimization algorithms typically used to solve optimization problems. We discuss the efficacy of our proposed method using four test problems to illustrate how the satisficing strategy outperforms the optimizing strategy in model-based engineering design. [ABSTRACT FROM AUTHOR]

In this study, we investigated autonomous vessel obstacle avoidance using advanced techniques within the Guidance, Navigation, and Control (GNC) framework. We propose a Mixed Integer Linear Programming (MILP) based Guidance system for robust path planning avoiding static and dynamic obstacles. For Navigation, we suggest a multi-modal neural network for perception, demonstrating the identification of obstacle type, position, and orientation using imaging sensors. Additionally, the paper compares an error-based PID control strategy and a Model Predictive Control (MPC) scheme as well. This evaluation aids in better evaluating their performance and determining their applicability within the GNC scheme. We detail the implementation of these systems, present simulation results, and offer a performance evaluation using an experimental dataset. Our findings, analysed through qualitative discussion and quantitative performance indicators, contribute to advancements in autonomous navigation and the control strategies to achieve it. [ABSTRACT FROM AUTHOR]

Testability design is an important cutting-edge technology to improve system reliability, safety, maintainability and supportability, which determines the failure detection and isolation rates and directly affects system maintenance (testing) cost. The testability design of the system has gone through a variety of design strategies, such as structural design, modeling design, and data driven design. Among them, data-driven based design is a rising strategic emerging strategy. They model the relationship between system tests and faults, and infer faults from test results to form diagnostic strategies. This paper firstly reviews the development process of system testability design and then focuses on the latest progress of testability scheme design including structure-based, model-based and data-driven-based schemes. After that, research status of each approach are sorted out and summarized. Then, the construction of the test diagnostic strategy is introduced, and the construction technology of the diagnostic strategy is determined according to the modeling method of the testability scheme, and the research on each type of technology is summarized. Finally, the current challenging problems and possible future research directions are discussed. [ABSTRACT FROM AUTHOR]

The problem of traffic control is solved using a model-based method. Automaton formalism is proposed for the development of a mathematical model. The states of a deterministic finite automaton (DFA) and the predicates of directed transitions are defined in strict accordance with the conditions of the problem. To implement the DFA, we used the Harel diagram (statechart); this is unified mathematical and software support for modern global modeling tools. The solution to the problem is proven constructively by a table of states with the corresponding dynamics and computational experiments of the selected scenario in advanced Russian and foreign instrumental environments for modeling the class of event systems. Computational experiments are in good agreement with constructive analysis. [ABSTRACT FROM AUTHOR]

Smart materials are upcoming in many industries due to their unique properties and wide range of applicability. These materials have the potential to transform traditional engineering practices by enabling the development of more efficient, adaptive, and responsive systems. However, smart materials are characterized by nonlinear behaviour and complex constitutive models, posing challenges in modelling and simulation. Therefore, understanding their mechanical properties is crucial for model-based design. This review aims for advancements in numerically implementing various smart materials, especially focusing on their nonlinear deformation behaviours. Different mechanisms and functionalities, classification, constitutive models and applications of smart materials were analyzed. In addition, different numerical approaches for modelling across scales were investigated. This review also explored the strategies and implementations for mechanically intelligent structures using smart materials. In conclusion, the potential model-based design methodology for the multiple smart material-based structures is proposed, which provides guidance for the future development of mechanically intelligent structures in industrial applications.

This work explores the innovative use of copper-alginate (Cu-alginate) hydrogels within microfluidic systems to catalyze dipolar cycloaddition reactions, emphasizing green chemistry principles and process intensification. Utilizing naturally occurring biopolymers, such as alginates, provides an environmentally friendly alternative to conventional catalyst supports due to their biocompatibility, biodegradability, and effective metal ion immobilization capabilities. The integration of these biopolymer-based catalysts into microfluidic devices allows for precise control over reaction conditions, leading to enhanced reaction kinetics and mass transfer efficiencies. Our results demonstrate that Cu-alginate hydrogels effectively catalyze the formation of 1,4-disubstituted 1,2,3-triazoles through [3 + 2] dipolar cycloaddition reactions with high regioselectivity and conversion. The microfluidic setup ensures rapid and efficient synthesis, surpassing traditional batch reaction methods in both reaction rate and environmental impact by reducing solvent usage and waste generation. Furthermore, the use of microfluidics contributes to the reproducibility and scalability of the synthesis process, important for industrial applications. The model-based design and its simulations have been employed to further understand and optimize the reaction system. Diffusion through the gel layer and catalytic reaction kinetics estimated from experimental data were included in the model, providing a theoretical foundation for a comprehensive process evaluation. This study not only advances the field of sustainable catalysis by demonstrating the practical utility of biopolymer-supported catalysts in microfluidic systems, but also sets the stage for further research into biopolymer applications in complex chemical syntheses.

The mathematical model of 6-DoF dynamics is used in different applications. In general, software-based solutions are utilized to implement the 6-DoF dynamic model. This paper introduces the FPGA-based implementation of the 6-DoF dynamics accelerator. The proposed hardware-based approach ensures the accuracy of the nonlinear model without compromising computational speed. The model-based approach and high-level synthesis have been employed in the design and implementation stages. Regarding design strategy, standard processor architecture, and resource-sharing methods have been applied to achieve FPGA resource efficiency. Seven datapath and finite state machines have been designed for seven different subsystems. The design resulted in hardware blocks that can execute all non-linear model equations 396 times in 1 ms using fixed/floating-point hybrid case and 434 times using pure fixed-point case. The model equations, which took an average of $\mathbf {0.4986}$ s to simulate in the Simulink environment, have been run on an FPGA in $\mathbf {7.1924}~\mu \text{s}$ . For seven design cases, numerical errors, resource utilization, and timing metrics are tabulated and presented to the reader.

This paper presents an advanced vertical control system using active suspension to stabilize the vertical motion of an in-wheel motor-driven electric vehicle. The design of the control system and conceptualization were carried out by mathematical modeling with integration with the quarter car model. A novel active suspension is developed through the model-based design to control the vehicles to move smoothly and continuously. Even though experimental validation is an effective and more accurate method to evaluate the control system, it is important to reduce the dependency on physical testing. Thus, a reliable simulation framework would be beneficial in the vehicle development process. In this paper, the hydraulic system is designed and simulated by using the Simcenter Amesim. For the dynamic vibration absorber, we are seeking to design a skyhook control to control the damping force by an electric damper, whereas the spring stiffness can be switched by opening and closing the fluid passage to the gas chamber. In the spring stiffness control, the stiff suspension can reach a ratio of 1.3 compared to the soft suspension. The objective of this research work was realized with the proposed simulation framework to test the effectiveness of suspension control system to improve ride and handling in a four in-wheel motor-driven electric vehicle.

As control algorithms evolve, their enhanced performance is often accompanied by increased complexity, reaching a point where practical experimentation becomes unfeasible. This situation has led to many theoretical studies relying solely on simulations without experimental verification. To address this gap, this study introduces a rapid experimentation protocol (REP) for applying field-oriented control (FOC) strategies to permanent magnet synchronous motors (PMSMs) based on model-based design (MBD) and automated code generation. REP is designed to be user-friendly and straightforward, offering a less complex and more accessible alternative to DSP toolboxes. Its excellent hardware compatibility is conducive to code porting and development. With this protocol, users can quickly conduct FOC strategy experiments with reduced dependency on the complex automated code generation tools often associated with toolboxes. Centered around the PMSM model, this method utilizes only the fundamental modules of MATLAB2023b/Simulink, greatly simplifying the user experience. To demonstrate the feasibility and efficiency of the protocol, models for both sensor-based and sensorless control are developed. The practicality of REP, including sensor-based and sensorless experiments, is successfully validated on an arm-cortex-M4-based GD32 microcontroller. [ABSTRACT FROM AUTHOR]

Fault detection, isolation and recovery subsystems are accepted to make safety-critical systems resilient against faults and failures. Yet, these subsystems should be devised only for those faults that violate the system's requirements, while providing a correct approach such that requirements are met again. Consequently, the obtained system is minimal, although complete, and robust both with respect to safety and performance requirements. In this paper, we propose a systematic and automated approach based on formal methods that includes (1) the evaluation of the relevance of faults based on quantitative risk assessment, and (2) the validation of system robustness by statistical model checking. We apply this approach on an excerpt of a real-life autonomous robotics case study, and we report on the implementation and results obtained with the S BIP framework. [ABSTRACT FROM AUTHOR]

Various examples show that stratified columns can improve the transport performance of particle packings. However, to date, there is no universal strategy to design these packings to yield optimal performance. This study proposes a model‐based approach for designing particle packings in which mass transfer occurs between a liquid phase and a stationary phase using optimal control theory. The primary objective is to provide a general design strategy that is applicable across different unit operations in chemical, pharmaceutical, and food applications. Optimal control is utilized to determine the optimal particle diameter as a function of the axial position within the column. We demonstrate the approach using two case studies and three different optimization criteria. Numerical results indicate that the proposed method is highly effective, for example, the solvent demand is reduced by up to 32.47%. Moreover, the optimally graded packing yields a significantly sharper breakthrough curve of an adsorption column. [ABSTRACT FROM AUTHOR]

Forward dynamics simulations can significantly reduce the development costs associated with new wearable assistive devices by minimizing the need for prototyping and experimentation. However, current model-based methods rely on experimental data to define the model posture for the simulation, making it challenging to design the wearer's posture suitable for reducing physical load with passive lower-limb assistive devices. To address this challenge, this study proposes a forward dynamics simulation method that focuses on optimizing physical posture. This simulation approach calculates human-device interactions, including reaction forces, physical posture, and physical load, based on the physical posture optimized by a cost function that evaluates both the physical load and the suitability of the posture for work, which contributes to estimating the impact of the device on the physical load of the wearer. To investigate the validation and advantage of the proposed simulation, this study compared the simulation and experimental results for existing and new passive lower-limb assistive devices. The results show that although the proposed method did not accurately simulate the individual human-device interactions for a given participant using the passive lower-limb assistive device, it accurately estimated the average reaction forces and lower limb posture across all participants. Additionally, the proposed method correctly represented the differences in reaction forces and lower limb posture resulting from changes in device structure. Consequently, the proposed simulation has advantages in computationally evaluating the device’s performance in reducing the lower limb loads and contributes to the development of effective assistive devices for preventing musculoskeletal disorders.

The development of electric gerotor pumps is a complex multiphysical optimization problem. To develop optimal systems, accurate simulation models are required to increase digital reliability. An important challenge is the accurate prediction of the pump behavior for extreme temperatures in automotive applications from −40 °C to 110 °C, where the viscosity of the fluid changes significantly. Therefore, simulation-based methods (numerical methods for calculating viscous friction) were developed and validated by measurements, including climatic chamber tests. The results show a strong correlation between simulated and measured performance characteristics, especially in terms of volumetric flow rate (<5%), pump torque and efficiency (<7%) at different temperature and viscosity conditions over a wide speed range (1000–5000 rpm) and different system pressures (0.5–5 bar). A novel method for simulating the cold start behavior of pumps (journal bearing approach for outer gear in pump housing) was introduced and validated by measurements. The methods presented significantly reduce the need for physical testing and accelerate the development process, as the pump behavior at each operating point can be accurately predicted before a hardware prototype is built. This improves the understanding of gerotor pump characteristics and provides insights to further improve the model-based development of electric oil pumps for the automotive industry.

This study introduces a robust model-based framework designed for the verification and validation (V&V) of Attitude Determination and Control Systems (ADCSs) in nanosatellites, focusing on magnetic actuation while still being applicable to larger spacecraft platforms. By employing Model-in-the-Loop (MIL), Software-in-the-Loop (SIL), Processor-in-the-Loop (PIL), and Hardware-in-the-Loop (HIL) methodologies, this framework enables a thorough and systematic approach to testing and validation. The framework facilitates the assessment of long-term maneuvers, addressing challenges such as initial small-attitude errors and restricted 3D movements. Two specific maneuvers are evaluated: detumbling and nadir pointing, utilizing quaternions and a comprehensive suite of sensors, including six sun sensors, a three-axis magnetometer, a three-axis gyroscope, GPS, and three magnetorquers. The methodologies—MIL, SIL, PIL, and HIL—integrate the behaviors of digital sensors, analog signals, and astrodynamic perturbations. Based on an optimized SIL environment, Monte Carlo simulations were performed to optimize control gains for nadir pointing, achieving a mean pointing accuracy of 11.69° (MIL) and 18.22° (PIL), and an angular velocity norm of 0.0022 rad/s for detumbling. The HIL environment demonstrated a mean pointing accuracy of 9.96° and an angular velocity norm of 0.0024 rad/s. This comprehensive framework significantly advances the design and verification processes for nanosatellite ADCSs, enhancing the reliability and performance of nanosatellite missions.

The present paper provides a comparison of different optimization techniques applied to the model-based design of a Buck Zero Voltage Switching (ZVS) Quasi-Resonant DC-DC Converter. The comparison was made both on the basis of the duration of the optimization procedures and in terms of guaranteeing the performance of the power electronic device. The main task of the paper is to present various techniques based on the use of mathematical software for the optimal design of Quasi-Resonant DC-DC converters. These topologies were chosen because in them, the design is carried out according to computational procedures, in which several iterations are often necessary for the successful completion of the process. An optimization procedure with a target function reference curve of the output voltage was used. In this way, the optimization is performed without the need for a complete design of the device but only by using base ratios, design constraints, and past experience to determine initial values and intervals of change in circuit parameters. This is also the main advantage of the used optimization of the reference curve type of the output, compared to applying other objective functions, such as achieving minimum losses or maximum efficiency of the device. [ABSTRACT FROM AUTHOR]

The electro-hydraulic actuator (EHA) system applied in rear axle steering (RAS) is used to steer the rear auxiliary wheels of large commercial vehicles and prevent oversteering. For safety reasons, commercial vehicles reduce the steering angle as the load applied to the rear wheels increases or the speed of the vehicle increases. In this study, we present a well-composed model based design (MBD) of an RAS system employing EHA used in large commercial vehicles. In order to apply loads to the rear of the vehicle to validate the legitimacy of the modeling and to replace the actual model's experiments with the simulations, the rotational speed of the motor obtained in the experiment was input to the motor of the simulation model. The organized formulas of the steering angle based on the structural form were defined to compare the steering angle against both the cylinder displacement of the actual model and the simulated model. We also applied load working on the steering wheel to check the angle difference according to the weight. The organized formulas were applied in the MBD system to compare the results of simulation modeling with the actual experimental values to confirm the modeling's validity. [ABSTRACT FROM AUTHOR]

The approach described in this paper handles the parameters and characteristics (analog and discrete ones) of a Buck DC-DC converter (in its power and control parts) in a common manner. The usage of probably complicated differential equations for discrete dynamical systems is avoided by means of index matrix equations, which can be easily understood. Compared to classical matrix models, the proposed index matrix models are more descriptive and also smaller in size. Such functionality is widely applied by the authors, and a new operation is defined and used as well. The relevance of the proposed techniques in power electronics, because of switching topologies and a limited numbers of components, is argued. Respective examples of functioning modes of the considered converter, in which power circuits and controllers are modeled jointly, are given. Estimations of analog values are based on partly linear dependencies, which are shown to be adequate in first-order analyses. Specific expressions for a Buck DC-DC converter are presented. A model-solving technique and an exhaustive search on a parameter space are considered in detail and automated via well-formalized algorithms. Nested parameter intervals and verifications with normal probability distributions are used in an optimization procedure. The full agreement of implementation via MATLAB source code with results obtained via Simulink is demonstrated. The short simulation times of this software (compared to Simulink and a.NET desktop application developed by the authors) justify the search for optimal variants in a wide multi-dimensional space. A max–min procedure with 10,000 simulations in each verification step is presented. [ABSTRACT FROM AUTHOR]

Featured Application: Mechatronics control and control engineering. The modeling and control of complex, non-linear, and time-changing mechatronic systems requires complex software development. They are carried out in the prototyping phase with engineering software development tools, generating models, and control algorithms that are not always easily exportable to control hardware. The following work offers an alternative that considers Model-Based Design using graphics-based languages, which facilitates programming tasks for modeling and controlling mechatronic devices and their transition from prototype to control hardware. Model-Based Design with high abstraction programming level capabilities provides the user with a fast coding and testing environment, suitable for laboratory prototyping and subsequent transfer to commercial embedded controllers. The proposed solution combines control hardware based on an STM32H7 microcontroller and a software development environment using graphics-based languages developed for MATLAB. The result is a solution that integrates control hardware and software in a hardware-in-the-loop paradigm. This solution provides robust and energy-saving controllers and demonstrates that an advanced control algorithm can be set up in a critical safety-compliant low-cost embedded controller via a custom model-based design. Algorithms and tools are transferred to the controller without losing the advantages gained in the prototyping phase. Finally, experimental results implementing an adaptive controller in a DC motor and in a pneumatic system are shown to validate the system. [ABSTRACT FROM AUTHOR]

Industry 4.0 (I4.0) systems are often designed without sufficiently considering the needs of stakeholders and the organizational processes to be supported, leading to solutions that are socially and organizationally unsustainable. In this study, the notions of social and organizational sustainability were viewed from a micro-level perspective, referring to the ability of technology to sustain the concerns of people and work organization within the socio-technical system, as opposed to a macro-level perspective related to concerns outside the system. Through a literature review, this study shows that social and organizational sustainability is covered by principles originally proposed in agile software engineering. A set of core requirements for model-based design approaches were then derived from the agile principles, based on insights from design research and model theory. The requirements include (1) the coverage of function and behavior, (2) simplicity, (3) executability and (4) modularity. They were then used to evaluate an existing modeling approach—subject-oriented process modeling (S-BPM)—to demonstrate their applicability and usefulness. [ABSTRACT FROM AUTHOR]

Formal verification of cyber-physical systems (CPS) is challenging because it has to consider real-time and concurrency aspects that are often absent in ordinary software. Moreover, the software in CPS is often complex and low-level, making it hard to assure that a formal model of the system used for verification is a faithful representation of the actual implementation, which can undermine the value of a verification result. To address this problem, we propose a methodology for building verifiable CPS based on the principle that a formal model of the software can be derived automatically from its implementation. Our approach requires that the system implementation is specified in Lingua Franca (LF), a polyglot coordination language tailored for real-time, concurrent CPS, which we made amenable to the specification of safety properties via annotations in the code. The program structure and the deterministic semantics of LF enable automatic construction of formal axiomatic models directly from LF programs. The generated models are automatically checked using Bounded Model Checking (BMC) by the verification engine Uclid5 using the Z3 SMT solver. The proposed technique enables checking a well-defined fragment of Safety Metric Temporal Logic (Safety MTL) formulas. To ensure the completeness of BMC, we present a method to derive an upper bound on the completeness threshold of an axiomatic model based on the semantics of LF. We implement our approach in the LF Verifier and evaluate it using a benchmark suite with 22 programs sampled from real-life applications and benchmarks for Erlang, Lustre, actor-oriented languages, and RTOSes. The LF Verifier correctly checks 21 out of 22 programs automatically. [ABSTRACT FROM AUTHOR]

To address an electric vehicle’s magnetic emission problem, a model-based improvement strategy is proposed to avoid resource-intensive experimental diagnosis processes, thus achieving higher efficiency. Considering the electrical and structural characteristics of electric vehicles, a network model is developed to predict magnetic emissions. It decomposes the electronic power system into a global network and external circuit nodes according to electrical size. The Z-parameter is used to characterize the global network for the decomposition of impedance coupling so that the model parameters can be obtained separately using different methods. With this network model, an evaluation index is designed to measure the influence of technical factors on magnetic emissions by comprehensively considering their contributions and rooms for improvement. Engineers can directly determine the main interference source according to this evaluation score, and select a proper filter to attenuate the interference.

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The paper presents the design of a single-ended transistor zero-voltage switch (ZVS) parallel resonant DC-DC converter. Due to the use of a resonant inverter in the structure of the DC-DC converter, it is characterized by high efficiency and improved performance. On the other hand, due to the specifics of the power circuit operation, in the work, it is proposed to find the values of some of the elements of the circuit of the electronic converter to be carried out based on the application of optimization. To solve this task, various tools available in Matlab/Simulink have been applied, as well as author's programs specially developed for the purpose. The use of a hybrid method for the design of power electronic converters, which combines analytical and optimization approaches, is justified in cases where there is no adequate design procedure. With the increase in the complexity of the power topologies and their possible modes of operation, difficulties arise related to their design such as: assumptions and limitations in conducting the analysis and the corresponding methodologies based on this analysis; high order of the differential equations composing the mathematical models; need for highly qualified specialists in the field of design. The proposed approach does not negate the classical design methods based only on analytical ratios determined by analysis of power circuits, but complements and develops them with innovative ones based on the application of computational mathematics and information and communication technologies. [ABSTRACT FROM AUTHOR]

The research aims to recognize the potential of adopting the model-based design methodology to the development process of an LPG (liquefied petroleum gas) fuelling system. Changing regulations often force the modern development of internal combustion engines (Euro 7, CO2 reduction measures, etc.). With the definitive ban on new registrations of vehicles powered by internal combustion engines in Europe (planned for 2035), there is still ongoing development of the adaptation of the fuelling system to LPG. There is still market potential in adapting new internal combustion engines, usually equipped with direct injection systems, to reduce customers' cost of ownership of a vehicle. As the engineering process should be accelerated in the face of the variety of direct injection systems offered by OEMs (original equipment manufacturers), the model-based design methodology is proposed to make the development more effective. The article presents the SWOT analysis of this approach in the engineering process and the potential of the method in an LPG system development is concluded. [ABSTRACT FROM AUTHOR]

The paper presents a precise and efficient model of Double-Side Cooled (DSC) SiC MOSFET, which incorporates the dynamics of both electrical and thermal variables. It offers a suitable computational complexity for simulating transients in complex power converters. The objective is to define a model that enables multi-scale time simulations and facilitates rapid power converter design in system-level tools such as Simulink. Additionally, the model aims to achieve simulation accuracy comparable to device-level models for the next generation of SiC MOSFETs. The paper demonstrates the complete test bench measurement procedure for the device. This procedure is essential for experimentally extrapolating the intrinsic characteristics and developing a model-reduction approach based on electro-thermal modeling. The approach strikes a balance between computational complexity and level of detail. The proposed model has been seamlessly integrated into Simulink to simulate a 3-phase inverter for several grid cycles at the grid frequency. To evaluate the model’s validity, the predicted inverter performance is compared with experimental measurements. These simulations require significantly less time compared to those based on LTspice models.

Co-simulation is a key step in the development of today’s complex cyber-physical systems (CPS), specially in the integration and validation activities. However, performing a co-simulation involving models developed in different environments and possibly deployed in different platforms with mixed real-time and non real-time constraints is a challenging engineering task. A promising technology that could help overcome communication and synchronisation difficulties is the non-proprietary standard Distributed Co-simulation Protocol (DCP). This standard defines an application-level communication protocol, independent of the platform and the communication medium, that regulates the exchange of information between the co-simulation entities. This paper presents a co-simulation interface based on the DCP standard. It offers a novel approach to apply the DCP standard. Instead of using it as a model encapsulation mechanism, having to develop an specific DCP slave for each application, it is proposed to use it as a generic co-simulation interface. To this end, a Simulink library has been developed, allowing to connect models developed in Simulink with the outside world in an standardised way. Moreover, by exploiting the code generation potential of Simulink, a wide variety of devices become accessible, thus enabling x-in-the-loop simulations, which are commonly used tests in the verification and validation process of CPSs. This library has been tested in a soft real-time co-simulation application between a Simulink instance and an application running on a Xilinx Zynq Ultrascale+ System-on-Chip. As an additional contribution, an analysis of DCP synchronisation problems when simulating closed-loop systems composed of two slaves is performed. Finding that the main causes are the occurrence of random delays and that the simulations of the two slaves start at an arbitrary time. A possible solution to this problem is also presented.

As control algorithms evolve, their enhanced performance is often accompanied by increased complexity, reaching a point where practical experimentation becomes unfeasible. This situation has led to many theoretical studies relying solely on simulations without experimental verification. To address this gap, this study introduces a rapid experimentation protocol (REP) for applying field-oriented control (FOC) strategies to permanent magnet synchronous motors (PMSMs) based on model-based design (MBD) and automated code generation. REP is designed to be user-friendly and straightforward, offering a less complex and more accessible alternative to DSP toolboxes. Its excellent hardware compatibility is conducive to code porting and development. With this protocol, users can quickly conduct FOC strategy experiments with reduced dependency on the complex automated code generation tools often associated with toolboxes. Centered around the PMSM model, this method utilizes only the fundamental modules of MATLAB2023b/Simulink, greatly simplifying the user experience. To demonstrate the feasibility and efficiency of the protocol, models for both sensor-based and sensorless control are developed. The practicality of REP, including sensor-based and sensorless experiments, is successfully validated on an arm-cortex-M4-based GD32 microcontroller.