Settling Time Research Articles

OPTIMAL LOAD FREQUENCY CONTROL OF INTERLINKED NONLINEAR POWER SYSTEM INTEGRATED WITH SMES-TCSC AND HVDC

In this article Multi-Area Multi-Source Interconnected Power System (MAMS-IPS) incorporated with an Automatic Voltage Regulator (AVR) in both the areas is considered for Load Frequency Control (LFC) study. Nonlinearity such as Governor Rate Constraints (GRC), Governor Dead Band (GDB), and Boiler are introduced with the thermal reheat generating unit. The effect of energy storage device (SMES) and fact device (TCSC) on the dynamic responses of IPS is also tested. PD-PID controller is suggested along with PID/PI-PD controller for minimizing the Automatic Control Error (ACE). The parameters of the proposed controller are optimized through a nature-inspired algorithm (PSO). PD-PID is superior then other suggested PID/PI-PD controllers. Objective functions ITAE, IAE, ISE, and ITSE are taken into consideration for finding the optimized values of the suggested controller as well as of TCSC and SMES devices. A step load of 10% is applied in both IPS areas. The rigidness of the suggested controller is verified by varying the loading condition of the IPS. A 10% increment in step load form is introduced for each area. The effect of renewable energy sources such as solar and a wind unit is also taken into consideration in this article. Varying step input is applied to this renewable unit to absorb its effect on the output responses of MAMS-IPS. The superiority of the PD-PID controller is verified by comparing its result with the recently published optimal controllers results described in the literature. SMES helps in improving the dynamic responses of the MAMS-IPS. Based on performance indices and Settling-time (ST) results of proposed controllers are compared with each other. For commenting on the stability of the introduced Power system (PS) eigenvalue analysis is also conducted. MATLAB version 2018 @ simulation software is used for simulation and for creating .m files

Operation Scheme analysis of a multipurpose small modular reactor under cogeneration condition based on a once-through steam generator dynamic model

Highly flexible load requirements and cogeneration economy need to challenge the operation of a multipurpose small modular reactor cogeneration plant with once-through steam generators. Therefore, the present study develops a once-through steam generator dynamic model to analyze the multipurpose small modular reactor operation scheme under cogeneration conditions at different power levels. The once-through steam generator dynamic model is derived based on conversation equations using the moving boundary method. It is verified with RELAP5 results and open literature and the maximum relative error is 3.21 %. Three operation schemes are proposed for multipurpose small modular reactor cogeneration operation: Scheme 1 with constant steam pressure and average coolant temperature, Scheme 2 with constant steam temperature and pressure, and Scheme 3 with constant steam temperature and pure sliding steam pressure. Steady-state and dynamic characteristics with three operation schemes are simulated and investigated at three power levels: 100 %, 70 % and 30 %. The steady-state results show that Scheme 1 is more favorable for the primary loop, while Scheme 2 is beneficial to the secondary loop, and Scheme 3 can improve the thermal efficiency at low power level. The transient findings indicate that disturbances from the reactor side have a significant impact on the once-through steam generator and the minimum settling time is 3.3 s. Consequently, steam temperature control of once-through steam generator is achieved by regulating the control rods for Schemes 2 and 3, while steam pressure is suggested to be controlled by the feedwater valve for Scheme 1. For cogeneration conditions at 70 % power level, Scheme 2 can achieve the highest steam flow of turbine, the highest steam flow of steam extraction and the smallest steam specific volume, which are 87.88 kg·s−1, 28.96 kg·s−1, and 0.0503 m3·kg−1, respectively. Scheme 2 is recommended for high power levels under cogeneration operation. In contrast, Scheme 1 is more suitable for the condensing unit operation for low power levels.

Finite-time input-to-state stability and settling-time estimation of impulsive switched systems with multiple impulses

This paper investigates finite-time input-to-state stability (FT-ISS) of impulsive switched systems with multiple impulses. Some FT-ISS conditions, using Lyapunov method and dwell-time condition, are established for impulsive switched systems involving destabilizing and stabilizing impulses simultaneously. When constituent modes regulating continuous dynamics are FT-ISS and discrete dynamics involve destabilizing and stabilizing impulses, it is shown that, the FT-ISS is retained if impulsive-switching signal satisfies some dwell-time condition. When some constituent modes regulating continuous dynamics are not FT-ISS and discrete dynamics involve destabilizing and stabilizing impulses, it is shown that, the impulsive-switching signal which satisfies some dwell-time conditions can achieve the FT-ISS of system. In addition, the settling time can be derived conveniently for certain impulsive-switching signal that is formalized by dwell-time condition. The estimation of settling time presents a class of uniformity with respect to the impulsive-switching signals. Two examples are finally presented for the proposed FT-ISS results.

Standardized Assessment of Gravity Settling Human Body Models for Virtual Testing.

The increased use of computational human models in evaluation of safety systems demands greater attention to selected methods in coupling the model to its seated environment. This study assessed the THUMS v4.0.1 in an upright driver posture and a reclined occupant posture. Each posture was gravity settled into an NCAC vehicle model to assess model quality and HBM to seat coupling. HBM to seat contact friction and seat stiffness were varied across a range of potential inputs to evaluate over a range of potential inputs. Gravity settling was also performed with and without constraints on the pelvis to move towards the target H-Point. These combinations resulted in 18 simulations per posture, run for 800 ms. In addition, 5 crash pulse simulations (51.5 km/h delta V) were run to assess the effect of settling time on driver kinematics. HBM mesh quality and HBM to seat coupling metrics were compared at kinetically identical time points during the simulation to an end state where kinetic energy was near zero. A gravity settling time of 350 ms was found to be optimal for the upright driver posture and 290 ms for the reclined occupant posture. This suggests that reclined passengers can be settled for less time than upright passengers, potentially due to the increased contact area. The pelvis constrained approach was recommended for the upright driver posture and was not recommended for the reclined occupant posture. The recommended times were sufficient to gravity settle both postures to match the quality metrics of the 800 ms gravity settled time. Driver kinematics were found to be vary with gravity settling time. Future work will include verifying that these recommendations hold for different HBMs and test modes.

Distributed predefined-time optimal economic dispatch for microgrids

With the massive popularization of distributed generators, optimal economic dispatch has been a key optimization problem to maintain stable and efficient work of the whole system. In this paper, a new smooth reconstruction penalty function with continuous and piecewise linear differential is designed to deal with generation power constraints, which promotes to obtain a better suboptimal solution compared with the existing smooth penalty methods. A distributed predefined-time optimal economic dispatch strategy is presented by utilizing a time-based function. By employing the proposed strategy, the minimization of the generation cost with transmission loss under the power balance constraint and generation minimum/maximum constraints can be realized within a predefined settling time. The performance of the proposed optimization strategy is evaluated by simulations and hardware-in-the-loop experiments in terms of validity verification, robustness to load change and topology reconfiguration, plug-and-play functionality, and comparison with the existing results to illustrate the advantages of fast convergence and near optimal results.

Fixed-time consensus problem for uncertain multi-agent systems with continuous and intermittent control

This paper addresses the fixed-time consensus issue in uncertain multi-agent systems (MAS). It introduces novel estimation methods for the maximum settling time, which considers all controller components but may also have less conservatism than traditional methods. Based on these results, a distributed control scheme and the corresponding consensus criterion are proposed, enabling MAS to achieve a fixed-time consensus and provide a more accurate estimation of the maximum settling time than the traditional method. Additionally, a distributed intermittent control scheme is also provided to enable the MAS to solve the issue of practical fixed-time consensus and be controlled only in a series of disjoint periods. Moreover, considering the case where the MAS has no external disturbance, another distributed intermittent control scheme is introduced to achieve fixed-time consensus under a directed topology. Finally, the results are supported by numerical examples.

The Potential of Elephantorrhiza goetzei Seed Extract as a Coagulant for Household Drinking Water Treatment

ABSTRACTPoor access to adequate, clean, and safe water is one of the greatest world problems people encounter. There has been considerable attention in recent times toward the use of natural coagulants for water treatment. This study seeks to promote this by investigating the potential of Elephantorrhiza goetzei (E. goetzei) seed extract as natural coagulants for water treatment. This included the determination of key ingredients responsible for the coagulation process and optimal dosages for the removal of turbidity, fluoride, manganese, and iron. The residual content of organic matter in the treated water and the quality of sludge produced were also investigated. The methodology consisted of a proximate analysis procedure to investigate the active ingredient(s) responsible for coagulation and standard jar tests. Standard methods were used for the analyses. Coagulant dosages ranging from 0 to 300 mg/L at a rapid mixing speed of 120 rpm for 1 min, a slow mixing speed of 30 rpm for 15 min, and a settling time of 15 min were used for the jar test. The analysis of variance (ANOVA) using IBM SPSS Version 20 was conducted, and regression models were developed to determine the effect of coagulant dosage on turbidity, pH, total dissolved solids, fluoride, iron, manganese, chemical oxygen demand (COD), nitrogen, and phosphorus. The results obtained from the proximate analysis of E. goetzei seed extract show that values of 5.25%, 21.40%, 8.23%, 32.99%, 2.20%, and 29.93% were obtained for moisture, crude protein, crude fiber, fat, ash, and carbohydrate content, respectively. Moreover, seed extract of E. goetzei achieved removal efficiencies up to 94.8%, 50.1%, 90.0%, and 53.9% for turbidity, fluoride, iron, and manganese in water, respectively. The coagulant has the potential to achieve the desired World Health Organization (WHO) drinking water standards for turbidity, fluoride, iron, and manganese. The COD increased from 55.3 to 419.3 mg/L as the coagulant dosage increased from 0 to 100 mg/L. This could cause an unwanted rise in microbial activities, affecting the microbiological quality of the treated water. The total nitrogen and phosphorus concentrations obtained in the sludge at 100 mg/L were 0.343 and 0.194 µg/kg, respectively, and this compromises its attractiveness for agricultural reuse purposes.

Design of solar and energy storage systems fed reduced switch multilevel converter with flower pollination optimization

In the present situation, the growing use of power electronic devices and non-linear loads has led to power quality (PQ) issues, including harmonics and poor power factor, which adversely affect the distribution network. This study contributes a design of shunt active power filter, powered by solar energy and energy storage systems, to address these PQ issues. To minimize losses, a five-level reduced-switch voltage source converter has been considered. Additionally, a neural network-based reference signal generation method is used, eliminating the need for conventional synchronous reference frame and active-reactive power theories, along with their complex abc and αβ0 transformations. This work also includes the optimal selection of the shunt filter and the gain parameters for the proportional-integral-derivative (PID) controller used in the shunt and battery control system. These parameters, along with the weights and biases of the neural network, are optimally determined using a nature-inspired flower pollination optimization algorithm.The proposed system has three primary objectives: (1) stabilizing the voltage across the DC bus capacitor, (2) reducing total harmonic distortion (THD) and improving the power factor (PF), and (3) ensuring the power management under the varying irradiation and load conditions. The effectiveness of the proposed system is evaluated through three testing scenarios, with results compared to conventional SRF and pq methods using a proportional-integral controller (PIC). The analysis reveals that the THD for the case studies is 3.32 %, 2.93 %, and 3.98 %, significantly lower than the other techniques compared. Additionally, the PF is nearly at unity, with a lower settling time of 0.05 s for the DC bus voltage.

A comprehensive analysis and closed-loop control of a non-isolated boost three-port converter for stand-alone PV system

This study critically investigates analysis and control of non-isolated boost three-port DC to DC converter (TPC) forstandalone PV system. The converter is controlled such that regulates flow of power from PV array to load and batteries as storage devices.According to PV power, there are four operating modes of operation of converter. Simple reduced-order dynamic models of the converter in various modes of operation are obtained using state-space averaging and small-signal techniques. In this work, the controllers of the closed-loop scheme are designed and only two controllers are used to achieve output voltage regulation, and to extract maximum power from PV array under different operating conditions. Closed-loop system simulation is studied to verify the operation of converter with the designed controllers in different modes. Transition between modes is presented with solar radiation variation and change of connected loads. Experimental verification of control systems at different modes of operation is investigated. The experimental results show that the controllers can regulate the power flow between TPC three ports and regulate output voltage under PV irradiance variation and load changing. The controller shows good performance measures such as maximum settling time of 0.06 s, maximum steady-state ripples of ±0.8 %, and 99.3 % power efficiency.

An ADPLL-Based GFSK Modulator with Two-Point Modulation for IoT Applications.

To establish ubiquitous and energy-efficient wireless sensor networks (WSNs), short-range Internet of Things (IoT) devices require Bluetooth low energy (BLE) technology, which functions at 2.4 GHz. This study presents a novel approach as follows: a fully integrated all-digital phase-locked loop (ADPLL)-based Gaussian frequency shift keying (GFSK) modulator incorporating two-point modulation (TPM). The modulator aims to enhance the efficiency of BLE communication in these networks. The design includes a time-to-digital converter (TDC) with the following three key features to improve linearity and time resolution: fast settling time, low dropout regulators (LDOs) that adapt to process, voltage, and temperature (PVT) variations, and interpolation assisted by an analog-to-digital converter (ADC). It features a digital controlled oscillator (DCO) with two key enhancements as follows: ΔΣ modulator dithering and hierarchical capacitive banks, which expand the frequency tuning range and improve linearity, and an integrated, fast-converging least-mean-square (LMS) algorithm for DCO gain calibration, which ensures compliance with BLE 5.0 stable modulation index (SMI) requirements. Implemented in a 28 nm CMOS process, occupying an active area of 0.33 mm2, the modulator demonstrates a wide frequency tuning range of from 2.21 to 2.58 GHz, in-band phase noise of -102.1 dBc/Hz, and FSK error of 1.42% while consuming 1.6 mW.

Harmonized control framework for integrated hybrid microgrid and virtual power plant operation

This paper presents a novel approach in the realm of electric vehicle (EV) applications and renewable energy-based distributed generation (RE-DG) by proposing a unified DC/AC hybrid microgrid (HMG) system tailored for poultry farms. The system aims to streamline design complexity, minimize component requirements, and champion sustainability by seamlessly integrating wind and solar photovoltaic (PV)-based DGs. An innovative EV-based virtual power plant (VPP) concept is introduced to mitigate power intermittency and eliminate the need for energy storage and extra charging stations. To ensure synchronized operation, a Harmonized Control Framework (HCF) is devised, capable of managing both grid-following and grid-forming operations while adapting to dynamic conditions and non-linear loads. Rigorous software and real-time Hardware-in-the-Loop (HIL) testing demonstrate the proposed microgrid's exceptional power transfer capabilities, improved harmonic performance, rapid settling times, and superior voltage/frequency regulation compared to the conventional double-stage synchronous frame (DD-SRF) control approach.

Comparison between Genetic Algorithms of Proportional–Integral–Derivative and Linear Quadratic Regulator Controllers, and Fuzzy Logic Controllers for Cruise Control System

One of the most significant and widely used features currently in autonomous vehicles is the cruise control system that not only deals with constant vehicle velocities but also aims to optimize the safety and comfortability of drivers and passengers. The accuracy and precision of system responses are responsible for cruise control system efficiency via control techniques and algorithms. This study presents the dynamic cruise control system model, then investigates a genetic algorithm of the proportional–integral–derivative (PID) controller with the linear quadratic regulator (LQR) based on four fitness functions, the mean squared error (MSE), the integral squared error (ISE), the integral time squared error (ITSE) and the integral time absolute error (ITAE). Then, the response of the two controllers, PID and LQR, with the genetic algorithm was compared to the response performance of the fuzzy and fuzzy integral (Fuzzy-I) controllers. The MATLAB 2024a program simulation was employed to represent the system time response of each proposed controller. The output simulation of these controllers shows that the type of system stability response was related to the type of controller implemented. The results show that the Fuzzy-I controller outperforms the other proposed controllers according to the least Jmin function, which represents the minimum summation of the overshoot, settling time, and steady-state error of the cruise control system. This study demonstrates the effectiveness of driving accuracy, safety, and comfortability during acceleration and deceleration due to the smoothness and stability of the Fuzzy-I controller with a settling time of 5.232 s and when converging the steady-state error to zero.

Optimization of calcined eggshell as an effective coagulant for treating colloidal particles in complex effluents in the CPCP industry: mechanistic insights, scale-up design, and comparative analysis with alum

Highly turbid industrial effluent poses significant challenges to environmental sustainability. In this study, we investigated the optimal aggregation kinetics for the removal of colloidal and turbid particles in Cosmetics and Personal Care Products (CPCP) industrial effluent using calcined eggshell (CES) and industrial-grade aluminum sulfate as flocculants. The effluent characteristics were determined following ASTM specifications, and process optimization was carried out using a response surface design approach. The optimal operating conditions at a settling time of 3 min were found to be pH 8, 0.2 g/L dosage of CES, pH 10, and 0.3 g/L of alum dosage. The flocculation efficiencies of CES and alum were found to be 80% and 78%, respectively, demonstrating the effectiveness of both flocculants in removing colloidal particles and reducing turbidity in CPCP effluent. Mechanistic studies revealed that CES achieved particle removal through enmeshment and inter-particle bridging with a significant aggregation rate (1.3 × 10−7) and a lower floc breakup tendency (2.8 × 10−14) compared to alum-sweep flocculation. The hydrodynamics at a velocity gradient of 269s−1 ≤ G ≤ 29s−1 indicated spontaneous agglomeration within a flocculation period of ≤10 min, indicating rapid and efficient particle removal. The findings of this study justify the use of CES as a sustainable and effective option for the removal of colloid/turbid particles from CPCP effluent. The optimized operating conditions and mechanistic insights into the flocculation process contribute to establishing an optimized sedimentation geometry, with specified aspect ratio, detention time, hypothetical settling, and sludge depth for CES, ensuring the favorable stability of the finished CPCP effluent before discharge.

Comparative analysis of proportional, proportional–integral, and proportional–integral–derivative controllers for thermal regulation in a cylindrical cooling system with multiple O-Ring heat sources

This study is intended to determine the thermal management capability of different closed-loop controllers inside a cylindrical three-dimensional cooling system with multiple O-Ring type heat sources. The motivation for this research stems from the need for efficient thermal regulation in advanced cooling systems, which is critical for applications ranging from electronics cooling to industrial processes. The uniqueness of this study lies in its comprehensive evaluation of different controllers such as proportional (P), proportional–integral (PI), and proportional–integral–derivative within a geometrically complex cooling environment using a novel trial-and-error approach for tuning controller parameters. The observational domain is a hollow cylinder, and the four discrete heat sources are placed at regular intervals along the cylinder's longitudinal axis, with all the remaining walls insulated. At the center of the system is a temperature probe that measures and provides feedback to the control module to continuously compare it to a pre-specified setpoint temperature. The flowing fluid, air, enters through the semi-circular inlet at one end, whose velocity is controlled by a controller response, and is discharged through the semi-circular outlet at the other end at atmospheric conditions. This study uses the Galerkin finite element method, using proper initial and boundary conditions to solve the governing equations, namely, the Navier–Stokes and heat energy equations. We analyze the time-dependent behaviors of the cooling system by measuring controller responses such as overshoot, rise time, oscillation, steady-state error, and settling time. Additionally, the impacts of the Reynolds number (Re), Richardson number (Ri), and Grashof number (Gr) on the overall mean Nusselt number over time are observed to understand the influence of flow regulation due to the controllers' actions. This comprehensive analysis provides insights into the controllers' inlet flow control based on the set temperature at the probe's center location. A unique trial-and-error approach for selecting Kp and Ki values, which is crucial for controller analysis, is also presented. Based on the results, it can be inferred that increasing the Kp value from 0.003 to 0.010 ms−1 K−1 reduces the steady-state error from 40.8% to 13.97%. For a Ki value of 0.006 ms−2 K−1, the PI controller achieves a zero steady-state error with faster settling at 3.29 s, along with an overshoot of approximately 80.51%. Conversely, a lower Kd value of about 0.0001 mK−1 results in a reduction in the settling time and overshoot compared to the PI controller, while a higher Kd value ensures optimum stability with a higher settling time and a stable Nusselt number of 1.93. This trial-and-error approach to parameter tuning provides valuable insights into the design of controlled environments and the effective management of thermal conditions in various thermo-fluidic applications.

Advanced particle swarm optimization for efficient and fast global maximum power point tracking under partial shading conditions

Partial shading (PS) is a common issue in photovoltaic systems (PVs), and it can significantly reduce the system's output power. This paper presents the advanced particle swarm optimization (APSO) algorithm. APSO is designed to alleviate the challenges posed by PS in PVs in from where of effectiveness and stability speed so that it works to achieve and maintain the global maximum power point (GMPP) under PS conditions. It leverages persistent variables to store and track system states and iterations; it also includes checks to ensure that the duty cycle remains within specified bounds facilitating more effective optimization. Additionally, APSO optimizes solar panel duty cycles and velocities to converge toward an optimal solution to improve overall power generation efficiency and settling time. The results evaluation involves testing the performance of photovoltaic panels under three different shading scenarios and comparative analysis against recent Heuristic-optimization-based GMPP techniques, this study and comparative analyses demonstrate APSO's effectiveness and superiority in terms of high efficiency that reaches 99.85% and fast settling time of GMPP at less than 0.01 second across all test cases. APSO presents a promising solution for maximizing PV power output in the presence of partial shading.

Enhancement of frequency transient response using fuzzy-PID controller considering high penetration of doubly fed induction generators

In modern power systems, renewable-based power plant such as wind power system is integrated significantly. Among numerous types of wind power systems doubly fed induction generators (DFIG) is becoming favorable in the last few years. However, adding a wind power plant could give a new challenge to the power system, especially in frequency stability. Hence, it is important to control the frequency of the power system to be able to find its initial condition in every condition. Generally, the frequency of the power system can be controlled by using automatic generation control (AGC). AGC is used to maintain the balance between generating capacity and the load by adding integral control to the governor. However, with more and more wind power systems in the grid conventional AGC is unsuitable. Hence, it is important to have an advanced AGC based on the artificial intelligence method. This paper proposed the application of fuzzy-proportional integrator derivative (fuzzy-PID) for AGC in power systems considering the high penetration of wind power systems. From the simulation results, it is found that the proposed method can reduce the overshoot and accelerate the settling time of frequency better than using conventional AGC.

Design of intelligent cruise control system using fuzzy-PID control on autonomous electric vehicles prototypes

Electric vehicles provide a solution for using alternative fuels, namely, electricity. Electric vehicles are used for short distances and intercity travel over long distances, increasing the risk of accidents. Cruise Control is a technology embedded in vehicles to maintain stable speeds; this system will automatically adjust the vehicle's speed when motion changes cause changes in vehicle speed. This study aims to apply lidar sensors to detect distance in the Intelligent Cruise Control (ICC) system using the Fuzzy-PID control method. Testing results were obtained at safe distance inputs of 5, 6, and 7 meters with various object distances. All the tests were carried out; the response systems were obtained with an average settling time of 5 seconds and an average overshoot of 1.53%. Therefore, the proposed Fuzzy-PID method works well for controlling Intelligent Cruise Control systems in autonomous electric vehicle prototypes.

Improved fixed-time stability analysis and applications to synchronization of discontinuous complex-valued fuzzy cellular neural networks

This article mainly centers on proposing new fixed-time (FXT) stability lemmas of discontinuous systems, in which novel optimization approaches are utilized and more relaxed conditions are required. The conventional discussions about Vt>1 and 0<Vt⩽1 are no longer required. For the purpose of verifying the new lemmas, complex-valued fuzzy cellular neural networks (CVFCNNs) with discontinuous activation functions are studied with a nontraditional non-separation method, which could reduce the conservatism of the obtained results greatly. Besides, FXT synchronization is discussed simultaneously. When contrasted with the results of other similar prominent pioneering works nowadays, the accuracy of settling times (STs) is quite enhanced. At last, numerical simulations are conducted to demonstrate the validity and superiority of our established theoretical results.

Finite-time stability control with hardware-in-the-loop testing of a chaotic permanent magnet synchronous motor

Stability of Permanent Magnet Synchronous Motor (PMSM) is of prime importance for the successful operation of the drive system, which is found to be dependent on initial operating conditions showing chaotic characteristic. Therefore, the paper presents the stabilization of a chaotic PMSM system through the finite-time stability approach. From this aspect, three controllers have been developed which are effective for the suppression of machine chaotic behaviour. Proposed controllers are simpler and numerically stable in comparison with previous works. Furthermore, performance comparisons of the proposed controllers are also presented in term of their settling time and peak overshoot. Selection among the proposed controllers depends on the consideration of a particular operating index (settling time or peak overshoot) wherein, performance also varies on system parameter λ. Performance evaluation of proposed controllers has been presented in MATLAB environment. In order to validate the obtained MATLAB results, a real-time analysis has been carried out using Typhoon Hardware-in-the-loop (HIL) emulator. The comparison shows that both results follow the same trend and are closely coordinated with each other, which validates the proposed controllers.

Advanced Multi-Sampling PWM Technique for Single-Inductor MIMO DC-DC Converter in Electric Vehicles

Amongst the various topologies of multi-input multi-output (MIMO) DC-DC converters, single-inductor MIMO (SI-MIMO) converters have the advantages of a reduced component count, a simpler structure, and low cost. These converters are suitable in electric vehicle (EV) applications involving variable ports, essential for performing different functions. Digital control in SI-MIMO converters is promising for enhancing transient performance due to its numerous benefits. However, delays in digital control, particularly computational and pulse width modulation (PWM) delays, can negatively impact the performance of DC-DC converters. Multi-sampling and double PWM update methods can mitigate these control delays, but they often necessitate complex control schemes, adding computational burden. In this work, an advanced multi-sampling PWM technique, integrating sample shift and multi-sampling, is proposed while employing a simple digital PID control scheme. The proposed method was tested for a shared-switch SI-MIMO converter with battery discharging and charging modes in the MATLAB/Simulink environment and compared with the conventional single- and multi-sampling PWM methods. The results demonstrated that the proposed method significantly improved the converter performance, surpassing the conventional single- and multi-sampling PWM methods. In the battery discharging mode, utilizing the proposed method, the output voltage achieved a settling time of 0.075 s in response to a step change in its reference, significantly outperforming multi-sampling, which yielded a settling time of 0.124 s, and single sampling, which exhibited an even longer settling time of 0.898 s. It also demonstrated a minimal overshoot of 0.06 volts compared to 1.5 volts with multi-sampling during the step change in the input voltage. Similarly, in the battery charging mode, upon a step change in the reference output voltage, the proposed method effectively minimized the overshoot of the output voltage to 0.845 volts compared to 1.175 volts with multi-sampling, and it decreased the inductor current settling time to 0.296 s from 0.330 s recorded under multi-sampling. These findings underscore the potential of the proposed method in enhancing the digital control performance of SI-MIMO DC-DC converters in electric vehicles.