Off-line Simulation Research Articles

Wheel Torque Distribution Control Strategy for Electric Vehicles Dynamic Performance With an Electric Torque Vectoring Drive Axle

The ability of active chassis control for dynamic performance improvement of electric vehicles with centralized drive system is limited duo to the driving torque between two-side wheels always equally distributed. To solve this problem, this paper proposes a novel electric torque vectoring (TV) drive-axle and its torque distribution control strategy, which can realize the function of arbitrary distribution of the left/right wheel driving torque in the form of centralized drive, thereby improving the dynamic performance of the vehicle. First, the structure and torque distribution principle of TV drive-axle are analyzed theoretically. Subsequently, an accurate mathematical model of TV drive-axle is established based on bond graph theory. Next, a wheel torque distribution control strategy of TV drive-axle is proposed based on hierarchical control approach to improve the vehicle’s handling stability. Wherein, the target yaw rate motion tracking controller as the upper-level controller is designed based on the second-order super-twist sliding mode control (SS-SMC) algorithm, and the wheel drive anti-slip controller in lower-level is used to restrict possible wheels slipping. Finally, the off-line simulation and hardware-in-the-loop (HIL) experiment results suggest that the proposed novel TV drive-axle and control strategy can significantly improve the handling stability and steering flexibility of the vehicle.

Four-Channel Active Noise Control Modeling and Offline Simulation for Electric Bus Sound Quality Based on Two FxLMS Algorithms

Four-Channel Active Noise Control Modeling and Offline Simulation for Electric Bus Sound Quality Based on Two FxLMS Algorithms

Distributed Platform for Offline and Online EV Charging Simulation

Efforts to enhance electric vehicle (EV) charging processes have spurred the emergence of smart charging algorithms. However, these studies are intricate and costly, necessitating preliminary simulations to assess EV integration into power grids. Existing solutions to this issue tend to be limited to academia and proprietary systems. To address this, we propose a user-friendly and intuitive simulation tool employing a decoupled and flexible architecture. This architecture, achieved through open design and containerized microservices, streamlines maintenance, extension, and scalability. We substantiated the validity of our solution by simulating the charging infrastructure from an H2020 Research Project. Furthermore, we integrated our solution with an external system that executes smart charging algorithms. The proposed system yielded the desired results, enabling the project team to evaluate both the integration and algorithms, even amidst the COVID-19 lockdown.

A Comparative Study of Swarm Intelligence Metaheuristics in UKF-Based Neural Training Applied to the Identification and Control of Robotic Manipulator

This work presents a comprehensive comparative analysis of four prominent swarm intelligence (SI) optimization algorithms: Ant Lion Optimizer (ALO), Bat Algorithm (BA), Grey Wolf Optimizer (GWO), and Moth Flame Optimization (MFO). When compared under the same conditions with other SI algorithms, the Particle Swarm Optimization (PSO) stands out. First, the Unscented Kalman Filter (UKF) parameters to be optimized are selected, and then each SI optimization algorithm is executed within an off-line simulation. Once the UKF initialization parameters P0, Q0, and R0 are obtained, they are applied in real-time in the decentralized neural block control (DNBC) scheme for the trajectory tracking task of a 2-DOF robot manipulator. Finally, the results are compared according to the criteria performance evaluation using each algorithm, along with CPU cost.

Steering cooperative seamless gearshift control for centralized and distributed coupling drive intelligent electric vehicle

The centralized and distributed coupling drive system can improve vehicle economy and dynamics performance, but there exists obviously power interruption and shifting shock during mode switching. To overcome the problems, a steering cooperative seamless gearshift control is proposed. Based on the system configuration, the feasibility of seamless gearshift and the necessity of steering cooperative are analyzed, the vehicle dynamics model is established, the seamless gearshift controller and the steering cooperative controller are designed, and the control effect is verified by the off-line simulation and vehicle road test. The research results show that, with the proposed control strategy, the vehicle can keep the original driving force during the mode switching, the shifting shock is reduced by 65% compared with the power interruption gearshift control, the maximum lateral displacement is 5 cm and the yaw rate is less than 0.2°/s, which improves the gearshift comfort of passengers and ensures the driving stability of the centralized and distributed coupling drive intelligent electric vehicle.

A novel directional pilot protection independent of line parameters and boundary elements for MMC-HVDC grid

In MMC-HVDC grid, the pilot protection is generally used as the backup protection for dc line. And in some dc grids, it can be considered as the primary protection, such as in the system using MMCs with fault-handling capability. However, most of the existing dc line pilot protections are highly dependent on accurate line parameters or line boundary elements (e.g., dc reactor), whose implementation complexity problem and engineering universality problem still need to be researched. In this paper, a novel directional pilot protection for MMC-HVDC grid, based on the ratio of high-frequency and low-frequency measured impedances, is proposed. Compared with the existing methods, the proposed protection does not need to obtain line parameters previously, thus significantly reducing the engineering implementation complexity. In addition, the proposed method is independent of line boundary elements, thus being suitable for the dc grid with no boundary reactors (or very small). Finally, the off-line simulation test based on PSCAD and real-time simulation test based on RTDS are developed to prove the feasibility and superiority of the proposed method.

Nonlinear Behavioral Modeling and Real-Time Simulation of Electric Propulsion System for the High-Fidelity X-in-the-Loop Applications

The electric propulsion system (EPS) is an important enabling technology for electrified transportation. The short time-to-market of such a system relies on real-time simulation (RTS)-based efficient X-in-the-loop testing. To ensure high fidelity, the RTS should include the detailed behavior as much as possible while complying with the constraints of the model computing time. Therefore, a nonlinear behavioral real-time modeling approach is proposed for the EPS in this article, including the adaptive curve-fitting (ACF)-based device-level power electronics model and the nonlinear flux-linkage-based spatial harmonic (FLSH) PMSM model. The real-time models are designed and implemented on the NI FLEXRIO FPGA module. Ultralow RTS latencies are realized for the ACF power converter model and the FLSH PMSM model, which are 25 and 160 ns, respectively. The simulation accuracies are consistent with the off-line simulation tools. Moreover, the ACF model and the FLSH model are used in the RTS of a fuel cell electric vehicle (FCEV) EPS together with the generic fuel cell model, the battery model, and the vehicle dynamic motion model. The RTS results prove that the proposed EPS real-time model is an excellent candidate for RTS applications.

A study on hybrid active noise control system combined with remote microphone technique

This paper proposed a hybrid active noise control (HANC) system combined with virtual sensing technique. The Remote Microphone Technique (RMT) method was established in the time domain, and the optimal array of observation sensors of RMT method was determined by Genetic Algorithm (GA). Then with the pre-defined observation filter, a multichannel simplified HANC system combined RMT (msHANC-RMT) method was proposed. The off-line simulations were executed with the data collected from the tests in a semi-anechoic chamber. The results showed that the msHANC-RMT system had the similar control capability compared to the msHANC system in all noise conditions, which can further compress the peak frequency components in the noise spectrum that cannot be detected and controlled by the traditional feedforward ANC (FFANC) system. However, the msHANC-RMT system was more sensitive to delays compared to the FFANC system, once the additional delays exceeded several milliseconds, the feedback structure in msHANC-RMT system lost most of the control capacity.

Parameter-adaptive reference governors with learned robust constraint-admissible sets

Reference governors (RGs) provide an effective method for ensuring safety via constraint enforcement in closed-loop nonlinear control systems. When the system parameters are uncertain but constant, robust formulations of RGs that consider only the worst-case effect may be overly conservative and exhibit poor performance. This paper proposes a parameter-adaptive reference governor (PARG) architecture that is capable of generating safe trajectories in spite of parameter uncertainties, without being as conservative as robust RGs. The proposed approach employs machine learning on a combination of off-line simulations and on-line measurements to estimate parameter-robust constraint-admissible sets (PRCASs) that can be leveraged by the PARG. We illustrate the robust set learning and constraint enforcement qualities of the PARG using a two-dimensional electromagnetic actuator example, and further demonstrate the potential of the PARG on a vehicle case study for preventing rollover despite aggressive maneuvering.

Dynamic modeling, stability analysis and control of interconnected microgrids: A review

This paper reviews concepts of interconnected microgrids (IMGs) as well as compare and classify their modeling, stability analysis, and control methods. To develop benefits of isolated microgrids (MGs) such as reliability improvement and their renewable energy integration, they should be interconnected, share power, support the voltage/frequency of overloaded MGs, etc. Despite maximizing their benefits and decreasing weaknesses of isolated MGs, IMGs require maintaining stability in different operation modes and employing appropriate control methods. Moreover, a basic requirement for stability analysis and controller design is system modeling. Since many articles have addressed these topics on IMGs from different views, a comparison is necessary. Therefore, IMG dynamic modeling methods are classified and their main features and challenges are discussed. Then, stability analysis and control methods of IMGs are reviewed and compared. The provided review is supported by conceptual diagrams, classification tables, off-line and real-time simulations using MATLAB and OPAL-RT simulator for comparison. Furthermore, a data set is provided to study fundamentals as well as research gaps, which are addressed for future works.

Robust Control Strategy for Inductive Parametric Uncertainties of DC/DC Converters in Islanded DC Microgrid

Direct current (DC) microgrid consists of many parallel power converters that share load currents through the inductance of DC/DC converters. Usually, the inductance parameters are dependent on the physical implementation of the system, and their values may not match their nameplates. Such disparities could lead to unequal response characteristics of the system, which can potentially reduce the performances of the DC microgrid operation. This paper proposes a robust control strategy for inductive parametric uncertainties of DC/DC converters using an optimal control method with integral action. To achieve such a goal, the system model parameters with nominal values are transformed into parametric unmatched uncertainties to form a robust control problem, which is then transformed into a linear quadratic regulator problem. The inductance uncertainties are stabilized with the uncertainty dynamic algebraic Riccati equation (UDARE) using state feedback gain under linear quadratic regulator. The closed-loop control with integral action is adopted to achieve a steady-state error of zero on the DC-link voltage at any uncertainty of the inductive parameter, which subsequently ensures the equal load current sharing. Off-line simulations and real-time validations based on OpalRT have been conducted to demonstrate the effectiveness and robustness of the proposed robust control strategy.

Faster-Than-Real-Time Hardware Emulation of Transients and Dynamics of a Grid of Microgrids

Enhanced environmental standards are leading to an increasing proportion of microgrids (MGs) being integrated with renewable energy resources in modern power systems, which brings new challenges to simulate such a complex system. In this work, comprehensive modeling of a grid of microgrids for faster-than-real-time (FTRT) emulation is proposed, which can be utilized in the energy control center for contingencies analysis and dynamic security assessment. Electromagnetic transient (EMT) modeling is applied to the microgrid in order to reflect the detailed device processes of the converter and renewable energy sources, while the AC grid utilizes the transient stability modeling to reduce the computational burden and obtain a high acceleration value over real-time execution. Consequently, a dynamic power injection interface is proposed for the coexistence of the two simulation types. The reconfigurability and parallelism of the field-programmable gate arrays (FPGAs) enable the whole system to be executed in FTRT mode with 51 times acceleration over real-time. Meanwhile, three case studies are emulated and the results are validated by the off-line simulation tool Matlab/Simulink®.

Efficient Hydrodynamic Modelling of Urban Stormwater Systems for Real-Time Applications

Urban water drainage systems represent complex networks with nonlinear dynamics and different types of interactions. This yields an involved modeling problem for which different off-line simulation approaches are available. Nevertheless, these approaches cannot be used for real-time simulations, i.e., running in parallel to weather now- and forecasts and enabling the monitoring and automatic control of urban water drainage systems. Alternative approaches, used commonly for automation purposes, involve parameterized linear delay systems, which can be used in real-time but lack the necessary level of detail, which, in particular, is required for adequate flood risk prognostics. Given this setup, in the present paper, an approach for the effective modeling of detailed water drainage systems for real-time applications implemented with the open-source Storm Water Management Model (SWMM) software is addressed and exemplified for a part of the water drainage system of the city of Flensburg in northern Germany. Additionally, a freely available early-warning system prototype is introduced and used to combine weather forcast information on a 2-h prediction horizon with the developed model and available measurements. This prototype is subsequently used for data assimilation using the ensemble Kalman filter (EnKF) for the considered area in Flensburg.

A Fast North-Finding Algorithm on the Moving Pedestal Based on the Technology of Extended State Observer (ESO).

We propose a kind of fast and high-precision alignment algorithm based on the ESO technology. Firstly, in order to solve the problems of rapid, high-accuracy, and anti-interference alignment on the moving pedestal in the north-seeker, the ESO technology in control theory is introduced to improve the traditional Kalman fine-alignment model. This method includes two stages: the coarse alignment in the inertial frame and fine alignment based on the ESO technology. By utilizing the ESO technology, the convergence speed of the heading angle can be greatly accelerated. The advantages of this method are high-accuracy, fast-convergence, strong ability of anti-interference, and short time-cost (no need of KF recursive calculation). Then, the algorithm model, calculation process, and the setting initial-values of the filter are shown. Finally, taking the shipborne north-finder based on the FOG (fiber-optic gyroscope) as the investigated subject, the test on the moving ship is carried out. The results of first off-line simulation show that the misalignment angle of the heading angle of the proposed (traditional) method is ≤2.1′ (1.8′) after 5.5 (10) minutes of alignment. The results of second off-line simulation indicate that the misalignment angle of the heading angle of the proposed (traditional) method is ≤4.8′ (14.2′) after 5.5 (10) minutes of alignment. The simulations are based on the ship-running experimental data. The measurement precisions of Doppler velocity log (DVL) are different in these two experiments.

A Turbulence Model for Flight Simulation and Handling Qualities Analysis Based on a Synthetic Eddy Method

A turbulence model based on a synthetic eddy method (SEM) has been adapted for flight simulation purposes and coupled with a FLIGHTLAB helicopter simulation model. The SEM is based on the generation of a random distribution of turbulence-generating eddies within a control volume surrounding the simulated aircraft. Eddies are displaced by the flow and regenerated at the inflow as they leave the simulation domain. The model allows adjustment of turbulence intensity and frequency spectra, allowing for a more realistic representation of broadband turbulence. Compared to other random turbulence models, preserving the location of the eddies in the control volume automatically ensures that turbulence across different aircraft locations is automatically correlated. Off-line and piloted flight simulation assessments have been conducted to test the viability of the SEM concept in flight simulation. Results show that the turbulence model generates upsets in all aircraft axes resulting in higher workload requirements for the pilot.

Off-Line Hybrid Simulation Method on Train–Track–Bridge Coupling Vibration in High-Speed Railway

The technology of real-time hybrid simulation (RTHS), which is one of the methods to test the performance of train operation on bridge in recent years, has strict real-time requirements. Combined with the fixed-point iteration (FPI) algorithm, this paper developed an off-line iterative hybrid simulation (OIHS) method, avoiding real-time synchronization between numerical and physical parts in RTHS to reproduce train–track–bridge coupling-vibration (TTBV) of high-speed railway in laboratory. In OIHS, the physical train model was installed on the shake table, while the response of the numerical track–bridge structure was simulated. To improve the test reproduction accuracy of the TTBV in high-speed railway, based on the shake table inherent off-line iterative control which is reproduce the commands issued to the shake table, an outer loop off-line iterative controller was designed to form a double-layer off-line iterative control framework to correct the response error between the subsystems. Compared with traditional finite element analysis, the accuracy and efficiency of the OIHS method were validated by numerical simulation and shake table test. The results demonstrated that the OIHS method can solve the dynamic convergence problem of the train–track–bridge on high-speed railway accurately and efficiently.

The epistemology of thought experiments without exceptionalist ingredients

This paper argues for two interrelated claims. The first is that the most innovative contribution of Timothy Williamson, Herman Cappelen, and Max Deutsch (a.k.a., the intuition deniers) in the debate about the epistemology of thought experiments is not the denial of intuition and the claim of the irrelevance of experimental philosophy but the claim of epistemological continuity and the rejection of philosophical exceptionalism. The second is that a better way of implementing the claim of epistemological continuity is not Deutsch and Cappelen’s argument view or Williamson’s folk psychological view (i.e., off-line simulation). This is so because while the argument view makes the basis of the relevant classificational judgement evidentially too demanding; the folk psychological view makes it too weak and error-prone to count as an adequate explanation. Drawing from a certain reading of Aristotle’s Nichomachean Ethics that flowers in Miranda Fricker and John McDowell, I argue for the reason-responsiveness view. Like the extant views, the reason-responsiveness view vindicates the claim of epistemological continuity. But unlike the extant views, it does not share those problematic features. Further, I show that the reason-responsiveness view offers a way for champions of the claim of epistemological continuity to resist Avner Baz’s objection to the claim of epistemological continuity and his objection to the philosophical use of thought experiments while taking on board some attractive elements of his view.

Direct current grid‐based doubly‐fed induction generator wind turbines: Real‐time control and stability analysis

Commonly, a simple topology consisting of a single diode-rectifier and pulse-width-modulation (PWM) converter is used for the connection of the doubly-fed induction generator-based wind turbines (DFIG-WTs) to the DC grid, in which the rotor-side converter (RSC) and the stator diode-rectifier are linked to the common DC bus. But, this topology suffers from less flexibility due to the requirement of matching the stator nominal voltage with the DC grid. Hence, in this paper, a buck converter is added to the DFIG-WT topology and two methods are proposed to control the power converters, where in the first one, the RSC regulates the active power and stator flux linkage, and in the second one, the RSC regulates the DC bus voltage and stator flux linkage. Then, the small-signal stability and the performance of the DFIG-WT system with the mentioned control strategies are compared analytically and through the off-line simulations. At last, a real-time hardware-in-the-loop (HIL) emulation-based OPAL-RT is carried out to investigate the performance of the proposed control methods from a practical perspective.

Machine Vision-Based Method for Estimating Lateral Slope of Structured Roads.

Most of the studies on vehicle control and stability are based on cases of known-road lateral slope, while there are few studies on road lateral-slope estimation. In order to provide reliable information on slope parameters for subsequent studies, this paper provides a method of structured-road lateral-slope estimation based on machine vision. The relationship between the road lateral slope and the tangent slope of the lane line can be found out according to the image-perspective principle; then, the coordinates of the pre-scan point are obtained by the lane line, and the tangent slope of the lane line is used to obtain a more accurate estimation of the road lateral slope. In the implementation process, the lane-line feature information in front of the vehicle is obtained according to machine vision, the lane-line function is fitted according to an SCNN (Spatial CNN) algorithm, then the lateral slope is calculated by using the estimation formula mentioned above. Finally, the road model and vehicle model are established by Prescan software for off-line simulation. The simulation results verify the effectiveness and accuracy of the method.

Carbon Dioxide Transport Pipeline Systems: Overview of Technical Characteristics, Safety, Integrity and Cost, and Potential Application of Digital Twin

Abstract Carbon dioxide transport from capture to utilization or storage locations plays key functions in carbon capture and storage systems. In this study, a comprehensive overview and technical guidelines are provided for CO2 pipeline transport systems. Design specifications, construction procedures, cost, safety regulations, environmental and risk aspects are presented and discussed. Furthermore, challenges and future research directions associated with CO2 transport are sorted out including the large capital and operational costs, integrity, flow assurance, and safety issues. A holistic assessment of the impurities’ impacts on corrosion rate and phase change of the transported stream is required to improve pipeline integrity. The influence of impurities and the changes in elevation on the pressure drop along the pipeline need to be further investigated to ensure continuous flow via accurate positioning of pumping stations. Although the long-experience in oil and gas pipeline industry forms powerful reference, it is necessary to develop particular standards and techno-economic frameworks to mitigate the barriers facing CO2 transport systems. Digital twins (DT) have potential to transform CO2 transport sector to achieve high reliability, availability, and maintainability at lower cost. Herein, an integrated five-component robust DT framework is proposed for CO2 pipeline transport systems and the future directions for DT development are insinuated. Data-driven algorithms capable of predicting system's dynamic behavior still need to be developed. The data-driven approach alone is not sufficient and low-order physics-based models should operate in tandem with the updated system parameters to allow interpretation and result's enhancing. Discrepancies between dynamic system models, anomaly detection, and deep learning (ADL) require in-depth localized off-line simulations.