A simulation-driven prediction model for state of charge estimation of electric vehicle lithium battery.

Accurately predicting the state of charge (SOC) of lithium-ion batteries in electric vehicles is crucial for ensuring their stable operation. However, the component values related to SOC in the circuit typically require estimation through parameter identification. This paper proposes a three-stage method for estimating the SOC of lithium batteries in electric vehicles. Firstly, the parameters of the constructed second-order RC circuit are identified using the Forgetting Factor Recursive Least Squares (FFRLS) method. Secondly, an innovative approach is employed to construct a battery simulation model using modal-data fusion method. Finally, the predicted values of the simulation model are corrected using the unscented Kalman filter (UKF). Validation through datasets demonstrates the high precision of this method in parameter identification. Moreover, in the comparison of SOC prediction corrections with Particle Filter (PF), Extended Kalman Filter (EKF), and the proposed UKF on simulated prediction data and experimental test data. The proposed method achieves the lowest root mean square error (RMSE) of 0.0025 for simulation prediction data and 0.0186 for experimental test data. It also maintained its error within 5 % on actual data.

Simulation of transient response of PID controller in an automated electro-pneumatic system using a single-acting cylinder in a clinical ventilator.

Patients with COVID-19 are not eligible for any therapy. Patients who have had respiratory failure and are unable to provide oxygen via noninvasive means obtain supportive care in ICUs. Since the onset of the outbreak, every sick COVID-19 patient has received oxygen via a mechanical ventilator. This study describes and simulates the transient stability of systems in an automated pressure regulator utilizing a single-acting cylinder in a clinical ventilator. These components include horizontal controllers, control devices, connecting tubes, and PID for electro-pneumatic control. Increased system stability and nonlinearity in electro-pneumatic actuator systems are accomplished by the implementation of PID. The redesigned PID control architecture was enhanced with alternative acceleration feedback through the close loop with an integral control method to get the system stable. This introduces the standard value N from the outside vicious circle and applies a form control law to integrate all reference control supply through into the gadget. Even as proportional gain (Kp) gets increased, the controller output would increase proportionately while maintaining the exact degree of accuracy. A derivative term boosts the ability of the Kd regulator to "detect" malfunctions. The integral term of the Ki controller minimizes its set point distortion. The system was updated to make it feasible for transferrable knowledge and competencies by incorporating real industrial components. The completed fluid control system was simulated through FluidSIM, which is frequently helpful for educational purposes.

Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm.

This article outlines the input data and partial shading conditions employed in the replication model of Sequential Monte Carlo (SMC)-based tracking techniques for photovoltaic (PV) systems. The model aims to compare the performance of classical perturb and observe (P&O) algorithm, particle swarm optimization (PSO) algorithm, flower pollination algorithm (FPA), and SMC-based tracking techniques. The mathematical design and methodology of the complete PV system were detailed in our prior research, titled "Dynamic and Adaptive Maximum Power Point Tracking Using Sequential Monte Carlo Algorithm for Photovoltaic System" by Odat et al. (2023) [1]. The provided data facilitate precise replication of the output, saving significant simulation time. Additionally, these data can be readily applied to compare algorithmic results referenced by (Babu, T.S. et al., 2015; PrasanthRam, J. et al., 2017) [2,3], and contribute to the development of new processes for practical applications.

Vehicle Detection and Tracking with Roadside LiDAR Using Improved ResNet18 and the Hungarian Algorithm.

By the end of the 2020s, full autonomy in autonomous driving may become commercially viable in certain regions. However, achieving Level 5 autonomy requires crucial collaborations between vehicles and infrastructure, necessitating high-speed data processing and low-latency capabilities. This paper introduces a vehicle tracking algorithm based on roadside LiDAR (light detection and ranging) infrastructure to reduce the latency to 100 ms without compromising the detection accuracy. We first develop a vehicle detection architecture based on ResNet18 that can more effectively detect vehicles at a full frame rate by improving the BEV mapping and the loss function of the optimizer. Then, we propose a new three-stage vehicle tracking algorithm. This algorithm enhances the Hungarian algorithm to better match objects detected in consecutive frames, while time-space logicality and trajectory similarity are proposed to address the short-term occlusion problem. Finally, the system is tested on static scenes in the KITTI dataset and the MATLAB/Simulink simulation dataset. The results show that the proposed framework outperforms other methods, with F1-scores of 96.97% and 98.58% for vehicle detection for the KITTI and MATLAB/Simulink datasets, respectively. For vehicle tracking, the MOTA are 88.12% and 90.56%, and the ID-F1 are 95.16% and 96.43%, which are better optimized than the traditional Hungarian algorithm. In particular, it has a significant improvement in calculation speed, which is important for real-time transportation applications.

Research on Two-Stage Semi-Active ISD Suspension Based on Improved Fuzzy Neural Network PID Control.

To better improve the ride comfort and handling stability of vehicles, a new two-stage ISD semi-active suspension structure is designed, which consists of the three elements, including an adjustable damper, spring, and inerter. Meanwhile, a new semi-active ISD suspension control strategy is proposed based on this structure. Firstly, the fuzzy neural network's initial parameters are optimized using the grey wolf optimization algorithm. Then, the fuzzy neural network with the optimal parameters is adjusted to the PID parameters. Finally, a 1/4 2-degree-of-freedom ISD semi-active suspension model is constructed in Matlab/Simulink, and the dynamics simulation is carried out for the three schemes using PID control, fuzzy neural network PID control, and improved fuzzy neural network PID control, respectively. The results show that compared with adopting PID control and fuzzy neural network PID control strategy, the vehicle body acceleration and tire dynamic loads are significantly reduced after using the grey wolf optimized fuzzy neural network PID control strategy, which shows that the control strategy proposed in this paper can significantly improve the vehicle smoothness and the stability of the handling.

Development of a Low-Cost Artificial Vision System as an Alternative for the Automatic Classification of Persian Lemon: Prototype Test Simulation.

In the present research work, an algorithm of artificial neural network (ANN) has been developed based on the processing of digital images of Persian lemons with the aim of optimizing the quality control of the product. For this purpose, the physical properties (weight, thickness of the peel, diameter, length, and color) of 90 lemons selected from the company Esperanza de San José Ornelas SPR de RL (Jalisco, Mexico) were studied, which were divided into three groups (Category "extra", Category I, and Category II) according to their characteristics. The parameters of weight (26.50 ± 3.00 g), diameter/length (0.92 ± 0.08) and thickness of the peel (1.50 ± 0.29 mm) did not present significant differences between groups. On the other hand, the color (determined by the RGB and HSV models) presents statistically significant changes between groups. Due to the above, the proposed ANN correctly classifies 96.60% of the data obtained for each of the groups studied. Once the ANN was trained, its application was tested in an automatic classification process. For this purpose, a prototype based on the operation of a stepper motor was simulated using Simulink from Matlab, which is connected to three ideal switches powered by three variable pulse generators that receive the information from an ANN and provide the corresponding signal for the motor to turn to a specific position. Manual classification is a process that requires expert personnel and is prone to human error. The scientific development presented shows an alternative for the automation of the process using low-cost computational tools as a potential alternative.

Improving the composting process of a treatment facility via an Industry 4.0 monitoring and control solution: Performance and economic feasibility assessment.

The European Union has set ambitious targets for recycling and landfill disposal of urban waste by 2025 and 2035, respectively. Composting is considered one way to achieve these goals. This paper focuses on a case study of a compost industrial treatment facility to identify potential and economically feasible improvements for the process and the factory. Through a thorough analysis of the facility and its production process, a plant section suitable for reengineering intervention has been identified. A technological solution based on Industry 4.0 is proposed to facilitate the monitoring and control of the bio-oxidation phase. An economic and feasibility analysis of this investment has been carried out over a ten-year lifecycle, comparing it with the company's business plan. A hybrid simulation model has been implemented to simulate and evaluate the reengineered plant, revealing that the bio-oxidation phase can be shortened to an average of six days. This result suggests that the adoption of smart technologies to control these types of processes are desirable and should become a standard. The social and economic effects of this investment were also analyzed to evaluate how to reduce the fares keeping the investment still valuable for the community and the private entrepreneurs.

The experimental multi-arm pendulum on a cart: A benchmark system for chaos, learning, and control.

The single, double, and triple pendulum has served as an illustrative experimental benchmark system for scientists to study dynamical behavior for more than four centuries. The pendulum system exhibits a wide range of interesting behaviors, from simple harmonic motion in the single pendulum to chaotic dynamics in multi-arm pendulums. Under forcing, even the single pendulum may exhibit chaos, providing a simple example of a damped-driven system. All multi-armed pendulums are characterized by the existence of index-one saddle points, which mediate the transport of trajectories in the system, providing a simple mechanical analog of various complex transport phenomena, from biolocomotion to transport within the solar system. Further, pendulum systems have long been used to design and test both linear and nonlinear control strategies, with the addition of more arms making the problem more challenging. In this work, we provide extensive designs for the construction and operation of a high-performance, multi-link pendulum on a cart system. Although many experimental setups have been built to study the behavior of pendulum systems, such an extensive documentation on the design, construction, and operation is missing from the literature. The resulting experimental system is highly flexible, enabling a wide range of benchmark problems in dynamical systems modeling, system identification and learning, and control. To promote reproducible research, we have made our entire system open-source, including 3D CAD drawings, basic tutorial code, and data. Moreover, we discuss the possibility of extending our system capability to be operated remotely, enabling researchers all around the world to use it, thus increasing access.

Modeling, simulation and performance evaluation of a PVT system for the Kenyan manufacturing sector.

Manufacturing is an end-use sector that uses the most delivered energy, accounting for around 50% of all transported fuel globally and 40% of carbon dioxide emissions worldwide. Solar photovoltaic-thermal (PVT) energy can substitute the transported energy to meet thermal and electrical energy requirements, mitigating high energy costs and climatic problems. This research aimed to develop, simulate, and evaluate the capabilities of a solar photovoltaic-thermal system for potential use in Kenya's manufacturing sector. A multistage cluster sampling technique was used in the study to characterize the manufacturing industry. Additionally, a PVT system was simulated using MATLAB Simulink to ascertain the relationship of temperature and the PV electrical efficiency. The impact of incorporating a thermal collector into the PV system on electrical, thermal, and overall system efficiency, and also the system's potential for use in thermal processes in manufacturing, were assessed. From the characterization results, the agro-processing sector dominates with 35% representation, and the small-scale thermal energy category dominates at 80%. The simulation findings show that a small temperature increase leads to a small increment in short circuit current but a significant decline in open circuit voltage. As a consequence, the maximum power (Pmax) of the PV decreases, lowering its electrical efficiency. However, the integration of PV with thermal collector improved the electrical, thermal, and the entire system efficiencies by, 16.01%, 20%, and 36.13%, respectively. More than 75% of the electrical and thermal energy processes fall in the small energy category. Hence, the PVT system is suitable for small-scale low-to-medium heat thermal energy categories or as a substitute system for higher temperature processes to raise feed water temperatures and reduction of thermal energy cost. This study gives a new approach of the application of PVT system for thermal industrial applications.

The Validity of Sensors and Model in the Lane Change Control Process.

The paper demonstrates the validity of sensors and the model in the algorithm for a lane change controller. The paper presents the systematic derivation of the chosen model from the ground up and the important role played by the sensors used in this system. The whole concept of the system on which the tests were carried out is presented step by step. Simulations were realised in the Matlab and Simulink environments. Preliminary tests were performed to confirm the need for the controller in a closed-loop system. On the other hand, sensitivity (the influence of noise and offset) studies showed the advantages and disadvantages of the developed algorithm. This allowed us to create a research path for future work with the aim of improving the operation of the proposed system.

Laser Measurement and Numerical Simulation of Elastomer Stopper Motion during High-Altitude Shipping of Pharmaceutical Syringes.

During high-altitude shipping of pre-filled syringes, pressure differentials can cause the elastomer stopper to move unintentionally. This motion represents a risk to container closure integrity and drug product sterility. To understand and quantitate this risk, we combined high-accuracy laser measurements and numerical simulations of stopper motion. We tested the effects of syringe barrel siliconization, stopper design, syringe orientation, and altitude rate on stopper displacement; only the siliconization factor had a significant effect. Our observations were compared with two mathematical models based on Boyle's Law and a force balance approach. For well-lubricated syringes, stopper motion was reasonably predicted by Boyle's Law (residual ≤ 10%). When the lubricant amount was reduced, Boyle's Law failed to accurately predict stopper motion (residual ≈ 40%). To simulate stopper motion more accurately, we developed a dynamic model in MATLAB-Simulink to incorporate the dry and viscous friction inherent to the lubricated interference fit. Using a Coulomb-viscous subroutine, deviations from Boyle's Law were successfully explained in terms of the displacement, but the system dynamics were not fully accurate. The combination of laser measurements and numerical simulation has yielded unique insight into stopper motion during high-altitude shipping. These tools can provide valuable input to a risk-based drug development strategy to enable global distribution of pre-filled syringes.

Comparison of efficiency of various DC-DC converters connected to solar photovoltaic module.

In this paper, an attempt is made to build an effective solar photovoltaic (PV) system considering geographical aspects such as irradiance and temperature using the single-diode equation model. Furthermore, a comparative analysis of various DC-DC converters (buck, boost, inverting buck-boost, non-inverting buck-boost (NIBB), Cuk, and single-ended primary inductance converter (SEPIC)) connected to a solar photovoltaic (PV) module was conducted in order to determine the optimal combination of DC-DC converter and solar PV. Moreover, the R, L, and C parameters for the converters have also been proposed to gain optimum efficiency from the solar PV system, and it has been shown that increasing the resistance decreases the ripple value. Furthermore, it has been shown that Ns and Np values of 36 and 1, respectively, result in 199 W of output power from a solar PV module at the maximum power point (48 V). The obtained results show that NIBB and SEPIC simulations gave the best results, with efficiencies of 93.27% and 92.35%, respectively.

The Five-DOF Explosion-Removal Manipulator Based on Position and Velocity Feedforward Compensation Control.

The main problem with a robotic system arm is its sensitivity to time delays in the control process. Due to this problem, it is necessary to further optimize the control process of the system. One solution is to deal with the control accuracy and response speed issues of robotic arm joints, to improve the system's response performance and enhance the system's anti-interference ability. This paper proposes a speed feedforward and position control scheme for robotic arm joint control. The conclusion section shows that compared to traditional five-degree-of-freedom robotic arm systems, the addressed robotic arm control system has a lower tracking delay and better dynamic response performance. It can improve the system's response performance while also enhancing its anti-interference ability.

Practical Implementation of the Indirect Control to the Direct 3 × 5 Matrix Converter Using DSP and Low-Cost FPGA.

The popularity of multiphase drives is increasing due to the growing interest in drives with more than three phases. One promising topology is the multiphase matrix converters, which enable the implementation of a single-stage AC/AC power conversion system with bidirectional power flow capability. In this paper, we present the implementation of indirect control for a practical sample of the direct matrix converter. To reduce the overall cost of the control solution for these types of converters, we utilized low-cost FPGA and DSP. The usage of only DSP itself was not possible due to low number of available PWM output needed for 3 × 5 MxC driving. Another reason is commutation, which must be precise and fast to avoid any hazardous states in the converter. Due to these problems, the authors decided to implement an algorithm of a combination of DSP and FPGA, where FPGA is used for time critical operations. The indirect algorithm treats the converter as two separate parts, the rectifier and the inverter, with the DC-LINK being fictitious. The matrix converter is composed of compact modules, and the entire system is verified. The practical verification demonstrates that matrix converters can produce a wide range of output frequencies and achieve input power factor control. Finally, we compare and review the practical model with the simulation model, examining efficiency and other parameters.

Clean Energy Based Multigeneration System for Sustainable Cities: Thermodynamic, and Stability Analyses.

This paper concerns the development and analysis of multigeneration systems based on hybrid sources such as biomass and wind. Industry requires different types of sources to provide several outputs, so the goal of this research was to fulfill the industrial requirement with optimization. The multigeneration cycle supplies enough power to satiate energy demands, i.e., power, cooling, hydrogen, air conditioning, freshwater, hot water, and heating. For this, the multigeneration cycle was modeled in the Engineering Equation Solver (EES) and Simulink to obtain optimized results for the industry. Energy and exergy for the multigeneration cycle were determined to assess the performance of the cycle and to investigate the optimized results for the overall system. This study shows that for configuration selection and design, different thermodynamic, economic, and environmental aspects should be considered. Based on the results, the selection of the best location for this multigeneration system was made. Power output from the wind turbine was around 7 MW and from biogas 0.6 MW. The overall exergy efficiency of the multigeneration system was found to be 0.1401.

Field oriented control dataset of a 3-phase permanent magnet synchronous motor.

This paper presents a dataset of a 3-phase Permanent Magnet Synchronous Motor (PMSM) controlled by a Field Oriented Control (FOC) scheme. The data set was generated from a simulated FOC motor control environment developed in Simulink; the model is available in the public GitHub repository. The dataset includes the motor response to various input signal shapes that are fed to the control scheme to verify the control capabilities when the motor is subjected to real life scenarios and corner conditions. Motor control is one of the most widespread fields in control engineering as it is widely used in machine tools and robots, the FOC scheme is one of the most used control approaches thanks to its performance in speed and torque control, with the drawback of having to handcraft the Proportional-Integrative-Derivative (PID) regulators using Look Up Tables (LUT). The test conditions are designed by setting a motor desired speed. Different input speed variations shapes are proposed as well as extreme scenarios where the linear behaviour of the PID regulator is challenged by applying fast and high magnitude speed variations so that the PID controller is not able to correctly follow the reference. The measured data includes both the outer and inner-loop signals of the FOC, which opens the possibility to develop non-linear control approaches such as Machine Learning (ML) and Neural Networks (NN) with different topologies to replace the linear controllers in the FOC scheme.

SimCOVID: Open-Source Simulation Programs for the COVID-19 Outbreak.

This paper presents open-source computer simulation programs developed for simulating, tracking, and estimating the COVID-19 outbreak. The programs consist of two separate parts: one set of programs built in Simulink with a block diagram display, and another one coded in MATLAB as scripts. The mathematical model used in this package is the SIR, SEIR, SEIRD, and SEIRV models represented by a set of differential-algebraic equations. It can be easily modified to develop new models for the problem. A generalized method is adopted to simulate worldwide outbreaks in an efficient, fast, simple, and visualized way. To get a good tracking of the virus spread, a sum of sigmoid steps was proposed to capture any dynamic changes in the data. The parameters used for the input (infection and recovery rate functions) are computed using the parameter estimation tool in MATLAB. Several statistic methods were applied for the rate function including linear, mean, root-mean-square, and standard deviation. In addition, an adaptive neuro-fuzzy inference system is employed and proposed to train the model and predict its output. Another program is presented for visualizing the COVID-19 data for each country worldwide in different dimensional views. The programs can be used as a teaching tool and for research studies.

Impact Analysis of Potential Induced Degradation on Crystalline Silicon Solar Cell Performance by Correlating Practical Diagnosis with MATLAB Simulation.

Extensive research on fault diagnosis is essential to detect various faults that occur to different photovoltaic (PV) panels to keep PV systems operating at peak performance. Here, we present an impact analysis of potential induced degradation (PID) on the current-voltage (I-V) characteristics of crystalline silicon (c-Si) solar cells. The impact of parasitic resistances on solar cell performance is highlighted and linked to fault and degradation. Furthermore, a Simulink model for a single solar cell is proposed and used to estimate the I-V characteristics of a PID-affected PV cell based on experimental results attributes. The measured data show that the fill factor (FF) drops by approximately 13.7% from its initial value due to a decrease in shunt resistance (Rsh). Similarly, the simulation results find that the fill factor degraded by approximately 12% from its initial value. The slight increase in measured data could be due to series resistance effects which were assumed to be zero in the simulated data. This study links simulation and experimental work to confirm the I-V curve behavior of PID-affected PV cells, which could help to improve fault diagnosis methods.

A portable and low-cost solution for real-time manipulation of the vestibular sense.

BACKGROUND: The vestibular system encodes head motion in space which is naturally accompanied by other sensory cues. Electrical stimuli, applied across the mastoid processes, selectively activate primary vestibular afferents which has spurred clinical and biomedical applications of electrical vestibular stimulation (EVS). When properly matched to head motion, EVS may also manipulate the closed-loop relationship between actions and vestibular feedback to reveal the mechanisms of sensorimotor recalibration and learning. NEW METHOD: We designed a portable, low-cost real-time EVS system using an Arduino microcontroller programmed through Simulink that provides electrical currents based on head angular motion. We used well-characterized vestibular afferent physiological responses to head angular velocity and electrical current to compute head-motion equivalent of real-time modulatory EVS currents. We also examined if our system induced recalibration of the vestibular system during human balance control. RESULTS: Our system operated at 199.997 Hz ( ± 0.005 Hz) and delivered head-motion-equivalent electrical currents with ∼10 ms delay. The output driving the current stimulator matched the implemented linear model for physiological vestibular afferent dynamics with minimal background noise (<0.2% of ± 10 V range). Participants recalibrated to the modulated closed-loop vestibular feedback using visual cues during standing balance, replicating earlier findings. COMPARISON WITH EXISTING METHODS: EVS is typically used to impose external perturbations that are independent of one's own movement. We provided a solution using open-source hardware to implement a real-time, physiology based, and task-relevant vestibular modulations using EVS. CONCLUSIONS: Our portable, low-cost vestibular modulation system will make physiological closed-loop vestibular manipulations more accessible thus encouraging novel investigations and biomedical applications of EVS.

Modeling and Simulation of Robotic Grasping in Simulink Through Simscape Multibody.

Grasping and dexterous manipulation remain fundamental challenges in robotics, above all when performed with multifingered robotic hands. Having simulation tools to design and test grasp and manipulation control strategies is paramount to get functional robotic manipulation systems. In this paper, we present a framework for modeling and simulating grasps in the Simulink environment, by connecting SynGrasp, a well established MATLAB toolbox for grasp simulation and analysis, and Simscape Multibody, a Simulink Library allowing the simulation of physical systems. The proposed approach can be used to simulate the grasp dynamics in Simscape, and then analyse the obtained grasps in SynGrasp. The devised functions and blocks can be easily customized to simulate different hands and objects.