Load Changes Research Articles

Investigation of DG units influence on 66 kV sub-transmission system network considering region load growth: a case study

Abstract Voltage breakdown in sub-transmission networks resulting from an increase in load demand can be addressed by incorporating distributed generation (DG) units such as hydro, wind, photovoltaic, and geothermal in some buses. This approach can lower power losses and the price of the primary generated energy while increasing network dependability and efficiency. Feasibility of dispersed generation integration & its effect on sub-transmission system operation were investigated using Ben Walied 66 kV sub-transmission network in Libya as a state. This study presents modified particle swarm optimization (MOPSO) technique to select the best option with dispersed generation units under various operating conditions. The Ben Walied 66 kV sub-transmission network has been subject of effects research on both normal operation and load growth scenarios. The goal of this study was to find best way to adjust penetration level of the three DGs in response to changes in the network loading. Three DG units have been refitted to study the effects on test networks for sub-transmission, which consist of 30 and 51 buses. A comparison analysis shows that while the ideal locations of DG units remain constant with load expansion, the optimal solution for the penetration level percentage of three DG units was boosted by new optimal sizes. Research has been done on how the power factor of distributed generators (DGs) affects the practical performance of 66 kV networks in steady-state conditions. The integration of DG units in regulating these losses and voltage variations is demonstrated by the results, which indicate that the ideal solution for DG unit’s power factor was at a value of 0.87 lagging.

An optimal demand side management for microgrid cost minimization considering renewables

AbstractIn an ordinary microgrid configuration, the required load changes from hour to hour. The power system firms determine the cost of energy at different times of day by considering the highest and lowest points of the consumption curve. This is referred to as time‐of‐use (TOU) pricing for power. The hourly basis load demand is divided into flexible and inflexible categories. Demand side management (DSM) lowers peak demand while rewarding customers for their participation based on load lowering. His rebuilds the whole load model on the pillars of demand cost movement. The research recommends a DSM methodology based on a combined intellect method to lower the total cost of employing loads in a microgrid (MG) structure while considering carbon tax as an unavoidable constraint to lower the emission of pollutants. This is because 40% of microgrid customers are willing to participate in the DSM scheme. The results obtained in each illustration demonstrate that the suggested DSM technique is suitable in terms of cost reduction. The generating cost was decreased from $15,488 to $15,354 when 0%–40% of clients engaged in the DSM programme. With just a 3% compromised increase in generation costs, a carbon price combined with economic emission dispatch reduced the pollutants emitted by up to 78%, from 70 to 15 tons.

Effect of changes in the centre of rotation after hip arthroplasty on knee joint function

Introduction: A common complication after hip arthroplasty is pain and inflammation in other large joints, especially the knee joint. Displacement of the centre of rotation of the femoral head after endoprosthetics can change the redistribution of force vectors acting on the femur, change its tilt and pressure on the surface of the knee joint. Objective: The investigation of the effect of displacement of the centre of rotation of the hip joint after arthroplasty on the knee joint.Methods: Using SolidWorks software and the SimulationXpress tool, a 3D model of the lower limb was created that reproduced the interaction between the components of the musculoskeletal system.Results: As a result, it was found that the displacement of the centre of rotation of the hip joint medially and laterally from the anatomical position leads to a significant increase in pressure on the corresponding tibial condyles. The increase in load is linear and increases from a minimum value of 1.77 N⋅m in anatomical position to 123.79 N⋅m with a medial displacement of up to 8 mm.Conclusions: This study indicates the need for proper restoration of the centre of rotation of the hip joint after implantation and the possible consequences of changes in knee joint loads. The data may be useful for specialists working in the field of implantology and the development of hip prosthesis systems

Bacteriophage P2-71: a promising therapeutic against multidrug-resistant Proteus mirabilis in urinary tract infections.

Proteus mirabilis is a Gram-negative, rod-shaped bacterium widely found in natural environments. It is known for causing a range of severe illnesses in mammals, particularly urinary tract infections (UTIs). This study evaluates the therapeutic efficacy of phage P2-71 against Proteus mirabilis in vivo and in vitro environments. The in vitro therapeutic potential of bacteriophage P2-71 was assessed through the ability of phage to kill Proteus mirabilis by using a plate counting assay, and biofilm inhibition and biofilm lysis assays using a microtitre plate method. Additionally, an in vivo UTI model in C57BL/6Jmice was developed via urethral inoculation of the bacterium. Phage therapy was administered through urethral injection over a period of 5 days. Therapeutic outcomes were measured by analyzing bacterial load, phage titer, inflammatory markers, and histopathological changes in the urine, urogenital tissues, and spleen. In vitro, bacteriophage P2-71 achieved significant reductions in P. mirabilis concentrations, with log reductions of 1.537 and 0.7009 CFU/mL in laboratory and urine environments, respectively (p < 0.001). The phage also decreased biofilm formation by 34-49% and lysed 15-25% of mature biofilms at various multiplicities of infection (MOIs) (p < 0.001). In vivo, phage treatment significantly lowered bacterial concentrations in the urine on Days 1 and 3 (p < 0.0001), achieving a maximum reduction of 4.602 log₁₀ CFU/mL; however, its effectiveness diminished by Day 5 (p > 0.05). Concurrently, phage titers decreased over time. Importantly, phage treatment notably reduced bacterial load in the bladder, kidneys, and spleen (p < 0.001). Inflammatory markers such as IL-6, IL-1β, and TNF-α were significantly lower in the treatment group, especially in the bladder (p < 0.0001), indicating an effective reduction in inflammation. Histopathological analysis showed significant mitigation of tissue damage. The results demonstrated that bacteriophage P2-71 is a promising alternative therapy for UTIs caused by MDR Proteus mirabilis. This bacteriophage therapy offers a viable strategy for managing infections where traditional antimicrobials fail, highlighting its potential in clinical applications.

Tumor infiltrating lymphocytes and change in tumor load on MRI to assess response and prognosis after neoadjuvant chemotherapy in breast cancer.

In this study, we aimed to explore if the combination of tumor infiltrating lymphocytes (TILs) and change in tumor load on dynamic contrast-enhanced magnetic resonance imaging leads to better assessment of response to neoadjuvant chemotherapy (NAC) in patients with breast cancer, compared to either alone. In 190 NAC treated patients, MRI scans were performed before and at the end of treatment. The percentage of stromal TILs (%TILs) was assessed in pre-NAC biopsies according to established criteria. Prediction models were developed with linear regression by least absolute shrinkage and selection operator and cross validation (CV), with residual cancer burden as the dependent variable. Discrimination for pathological complete response (pCR) was evaluated using area under the receiver operating characteristic curves (AUC). We used Cox regression analysis for exploring the association between %TILs and recurrence-free survival (RFS). Fifty-one patients reached pCR. In all patients, the %TILs model and change in MRI tumor load model had an estimated CV AUC of 0.69 (95% confidence interval (CI) 0.53-0.78) and 0.69 (95% CI 0.61-0.79), respectively, whereas a model combining the variables resulted in an estimated CV AUC of 0.75 (95% CI 0.66-0.83). In the group with tumors that were ER positive and HER2 negative (ER+/HER2-) and in the group with tumors that were either triple negative or HER2 positive (TN&HER2+) separately, the combined model reached an estimated CV AUC of 0.72 (95% CI 0.60-0.88) and 0.70(95% CI 0.59-0.82), respectively. A significant association was observed between pre-treatment %TILS and RFS (hazard ratio (HR) 0.72 (95% CI 0.53-0.98), for every standard deviation increase in %TILS, p = 0.038). The combination of TILs and MRI is informative of response to NAC in patients with both ER+/HER2- and TN&HER2+ tumors.

Investigation of ruthenium loaded beta zeolite catalyst performance in vanillin hydrodeoxygenation yielding both monomeric and dimeric cycloalkanes

The valorization of lignin-derived bio-oil is studied extensively due to its promising contribution to sustainability. Among these studies, many have focused on the hydrodeoxygenation (HDO) of phenolic model compounds as it is a crucial process in obtaining valuable oxygen-free hydrocarbons. In this work, vanillin HDO was performed on various bifunctional ruthenium-based zeolite catalysts with different zeolite supports (Y, ZSM-5, and beta) in a batch reactor. Ru-loaded beta zeolite catalysts (Ru/Hβ) exhibited the highest HDO activity among them, and the formation of dimeric cycloalkanes of high value were also observed specifically when using the Ru/Hβ catalyst. Due to their benefits of direct use in blending of biofuel, factors promoting the dimerization of phenolic monomers were extensively examined through a series of experiments using a mix of phenolic model compounds as HDO reactants. Specific oxygen containing functional groups contributed to the aldol condensation of aromatic species, and the structure and kinetic diameter of the monomers had a profound effect on the ability to participate in dimerization. Additionally, the metal loading of the catalyst and reaction conditions such as temperature and hydrogen pressure were varied to observe each of their effects on the product distribution. The change in metal loading had a remarkable impact on the preferred reaction pathway and product selectivity, while a high temperature of 200 °C and hydrogen pressure of 50 bar was determined to be necessary to fully achieve HDO to cycloalkanes. Consequently, this study has provided useful information on the production of both monomeric and dimeric cycloalkanes and has contributed to the development of the bio-oil upgrading process.

Development and verification of real-time hybrid model test delay compensation method for monopile-type offshore wind turbines

The real-time hybrid model (RTHM) test is adept at addressing the scale contradiction, the lack of fidelity in wind modelling in hydrodynamic testing facilities and spatial constraints inherent in conventional monopile-type offshore wind turbine (OWT) model testing methods, thus emerging as an effective avenue for conducting physical model tests of Monopile-type OWTs. This method entails the reproduction of aerodynamic loads or platform motions using loading device or vibration tables. Time delays in the physical attributes of the loading device and signal transmission processes within the system can result in error accumulation, with the potential to impact overall system stability. Moreover, time delay compensation algorithms for hybrid model test systems with force control loading can easily generate excessive noise, leading to system divergence. As a result, time delay has emerged as a technical challenge in the RTHM test. To address this issue, this paper has developed second-order and third-order polynomial extrapolation algorithms, alongside an adaptive compensation algorithm. The adaptive compensation algorithm employs the least squares method to identify parameters of the loading system, enabling it to address variations in the time delay of the experimental system caused by the nonlinearity of the loading system and changes in the physical properties of the model. The feasibility and effects of time delay compensation for various algorithms are validated through numerical simulation. Results indicate that the adaptive compensation algorithm surpasses second and third-order polynomial extrapolation compensation algorithms in terms of accuracy and compensation effectiveness. To validate the applicability of the adaptive compensation algorithm, a RTHM test was conducted. Across rotor thrust force (RotThrust) and tower top displacement, there was an average reduction of approximately 5 % and 9 % in the maximum and minimum synchronization errors, respectively. This highlights the efficacy of the delay compensation algorithm in practical applications, notably diminishing time delay errors within the experimental system. The adaptive compensation algorithm continuously adjusts and updates parameters, enhancing the adaptability of the compensation process to time-varying systems.

Contributions of mechanical loading and hormonal changes to eccentric hypertrophy during volume overload: a Bayesian analysis using logic-based network models.

Primary mitral regurgitation (MR) is a pathology that alters mechanical loading on the left ventricle and induces a distinctive ventricular remodeling response known as eccentric hypertrophy. Drug therapies may alleviate symptoms, but only mitral valve repair can provide significant recovery of cardiac function and dimensions. However, 20% of patients still develop systolic dysfunction post-operatively despite being treated according to the current guidelines. Thus, better understanding of the hypertrophic process in the setting of ventricular volume overload (VO) is needed to improve and better personalize the management of MR. To address this knowledge gap, we employ a Bayesian approach to combine data from 70 studies on experimental volume overload in dogs and rats and use it to calibrate a logic-based network model of hypertrophic signaling in myocytes. The calibrated model suggests that growth in experimental VO is mostly driven by the neurohormonal response, with an initial increase in myocardial tissue stretch being compensated by subsequent remodeling fairly early in the time course of VO. This observation contrasts with a common perception that volume-overload hypertrophy is driven primarily by increased myocyte strain. The model suggests that Endothelin1 receptor activity plays a central role in driving hypertrophic responses and the activation of the fetal gene program. The model reproduces a number of responses to drug therapy not used in its calibration, and predicts that a combination of endothelin receptor antagonist and angiotensin receptor blockers would have the greatest potential to dampen cardiomyocyte hypertrophy and dysfunction in VO.

Awareness-guided incremental control optimization for chilled water system with deep learning model under cold-start scenarios

For heating, ventilation, and air conditioning (HVAC) systems, the technology of optimal control can achieve significant energy savings by resetting the control setpoint in responding to the change of user load and weather condition. However, traditional method will fail in cold-start scenarios, in which the diversity of history data is limited. Under this case, significant prediction error will occur in extrapolation space, and the optimized control strategy cannot fully achieve energy saving potential or even increase energy consumption. To solve this problem, here we propose a novel awareness-guided incremental control optimization method. Its basic idea is to explicitly consider the prediction error of energy model during the control optimization process. The deep ensemble algorithm is firstly adopted to capture the prediction error. And the optimization process will be aware of such potential error, and make a tradeoff between conservative state and exploratory state. The control optimization process will start with the known optimal setpoint (conservative state) to achieve stable energy saving, and then gradually explores other unknown candidates (exploratory state) to achieve further energy saving. To validate our method, a virtual test bed of chilled water system is developed by Modelica language to compare fixed setpoint strategy, traditional method, and proposed method. The results demonstrate that the proposed method can avoid negative energy saving ratio during the early stage of control optimization. And it can also find optimal control strategy faster. Comparing with traditional method, the awareness-guided method can achieve further 2.9 % energy saving ratio, and the overall energy saving is between 6.1% and 13.9 %.

Molecular dynamics simulation and experimental verification of a biphasic solvent for CO2 capture

In the context of solvent-based carbon capture, researchers and industries are often interested in improvements in the efficiency of CO2 capture along with the reduction in the required energy. This study employs molecular dynamics (MD) simulation based on a reax force field and experimental investigation to study the effects and main mechanisms of a mutual amine absorbent including diethylenetriamine (DETA) and diethylethanolamine (DEEA), accompanied by NMP and water co-solvents, on the performance of CO2 capture in a phase change system. The implementation of time-dependent partial radial distribution functions (TD-PRDF, gαβrtm) and coordination number (CN) analyses revealed the significant formation of C-N bonds between carbon (C) derived from CO2 and nitrogen (N) within the solution. The direct relationship between changes in DETA molar ratios and CO2 loading, coupled with examining the catalytic role of DEEA in facilitating CO2 removal through protonation, has been thoroughly studied with MD. The experimental methodology was followed to validate the MD results. The optimum composition, DETA: DEEA: NMP with a molar ratio of 3:2.5:1, as determined through MD simulations exhibitsgαβr|tm = 9.848, CN=0.403 at tm= 1 ns. The stable C-N absorption bond length is calculated to be between 1.7 and 1.77 Å. Experimental results confirm a CO2 loading capacity of 0.93 mol/mol for this composition.

SENSORLESS SPEED ESTIMATION OF THREE PHASE INDUCTION MOTORS BASED ON DYNAMIC MODEL

In speed control systems of induction motor electrical drives, real-time speed monitoring is necessary. Speed monitoring can be done using the direct method, which uses a mechanical sensor mounted on the motor shaft, or the indirect method, which is based on estimation, mainly from the dynamic model of the motor. Speed estimation based on the dynamic model of the motor in orthogonal coordinates is the most widespread method in sensorless speed control systems of three-phase squirrel cage induction motor electrical drives, especially those of high accuracy. This paper presents the open-loop speed estimator used for speed estimation in three-phase induction motors. The proposed speed estimators are based on the orthogonal coordinate’s dynamic model of an induction motor in a stator reference frame. This technical solution is simple and has a low cost. The currents and voltages of the two motor phases are the input variables of the estimator, while the output variable is the induction motor speed. The speed estimator model is built using LabVIEW software. The dynamics and accuracy of the estimator proposed in this paper have been tested experimentally. The speed measured by the industrial incremental encoder is compared with that of a speed estimator modeled in LabVIEW software. The obtained experimental results show a good match between the measured and estimated speeds under the step torque load changes of the induction motor.

The comparison study of PI and Sliding Mode control techniques for Buck-Boost converters

This paper compares the performance of a Sliding Mode Control (SMC) and Proportional-Integral (PI) controller under different voltage and load conditions. The study's findings underscore the need to account for load variations in system designs and to continuously seek system optimization irrespective of the controller type chosen. PI controller demonstrates effectiveness under certain circumstances. However, significant drops in voltage and current during abrupt load changes are obtained. On the other hand, SMC enables superior adaptability, efficiently managing voltage transients and load variations without any electrical disturbances, thereby maintaining system stability. A comparative analysis further emphasizes the SMC's superior time response and robustness against reference voltage changes. Consequently, SMC is proven to be a preferable choice over the PI controller in systems experiencing frequent voltage and load variations. However, both controllers achieve the potential for further response time optimization and stability.

Study on photovoltaic primary frequency control strategy at different time scales

AbstractDuring the participation of photovoltaics in grid frequency regulation, different frequency regulation tasks are required at different time scales. The grid demands that photovoltaics (PVs) improve steady‐state frequency when facing short‐term load fluctuations, while also enhancing frequency response to long‐term environmental and load changes. Therefore, this study takes different time scales as the starting point. First, a two‐stage PV grid‐connected inverter generation system model is established, and an overall control strategy is proposed. Next, for short‐term time scales, a virtual inertia strategy based on direct current (DC) voltage droop control is proposed to utilize the energy storage effect of DC capacitors to suppress frequency fluctuations. For long‐term time scales, a strategy for controlling the variable reactive power reserve capacity is proposed to address the inadequacy of frequency regulation caused by traditional fixed de‐rating rate strategies and redundant standby power. Finally, the effectiveness of the proposed strategies is verified through model validation in MATLAB/Simulink. Simulation results demonstrate the effectiveness of the strategies at different time scales, aiding in improving grid frequency response.

Large‐signal stability analysis for hybridized vehicular power supply systems of rolling stocks

AbstractHybridized vehicular power supply (HVPS) are acquiring widespread adoption in various applications such as providing power for passenger or heavy‐duty electric vehicles, more‐electric ships, electrified rolling stocks, and more. Stability analysis is a critical issue for HVPS, but it presents significant challenges due to their prominent high‐dimensional and nonlinear characteristics. This paper presents a large‐signal stability analysis scheme for HVPS of rolling stocks, enabling the assessment of system stability under sudden load changes. Based on the state‐space averaging method, a mathematical model for the large‐signal behavior of the system is established. Subsequently, the small‐signal stability parameter range of the system is determined by analyzing the eigenvalues of the Jacobian matrix. To further analyze the stability of the system during large‐signal disturbances, a nonlinear decoupling transformation approach is employed to decompose the original high‐order state equations into multiple lower‐order equations. For the decoupled lower‐order subsystems, their stability is analyzed using phase portrait, and the region of attraction (ROA) is determined using the inverse trajectory method. Based on the stability analysis results, the controller is enhanced to bring the points outside the ROA back within it, thereby mitigating the transient instability phenomenon of the system. The effectiveness of the proposed method was demonstrated using two case studies.

Simulation and experimental analysis of dynamic thermal rise relaxation characteristics for dry-type distribution transformer

Abstract The temperature distribution characteristics of dry-type distribution transformers reflect their overall performance and quality. Distribution transformer daily load changes dramatically, its temperature fluctuates within a certain range. However, most of the research results on transformer temperature rise focus on the steady-state temperature characteristics of transformers, and lack of research related to dynamic temperature rise characteristics. This paper carries out a multi-physics coupling simulation and experimental verification of the dynamic temperature rise relaxation characteristics. The simulation uses the “electromagnetic-flow-thermal” multi-physics coupling analysis method to simulate the steady-state temperature rise characteristics and dynamic temperature rise relaxation characteristics of windings under different load rates. Then, this paper also explores the correlation between the dynamic temperature rise relaxation characteristics and load rate at the typical positions of high-voltage windings and low-voltage windings. The results show that the temperature rise of the winding shows the law of increasing the saturation index function with the increase of the load application time at any load rate. A quantitative characterization model of dynamic temperature rise relaxation behavior at different positions of transformer windings is constructed. It is found that the steady-state temperature rise value of different parts of the winding increases regularly as a power function with the increase of load rate, while the constant value of dynamic temperature rise relaxation time in different parts of the winding decreases as a power function with the increase of load rate. The verification results of the quantitative characterization model of dynamic temperature rise relaxation behavior show that the maximum error of the measured and theoretical steady-state temperature rise value is only 1.56 K, and the maximum error of the constant value of dynamic temperature rise relaxation time is only 0.082 h. These findings provide valuable insights into the performance and quality of dry-type distribution transformers, and can help improve their design and operation for better efficiency and safety.

A new optimal 3° of freedom fractional order proportion integral derivative controller with model predictive controller for frequency regulation in high penetrated renewable based interconnected system

The increasing use of renewable energy sources (RESs) in conventional power systems is making them more complex. RES, such as solar and wind energy, reduce system inertia, affecting power system (PS) stability and frequency aberrations. Thus, the modern PS faces new concerns that arise from integrating RESs and struggles to manage frequency and stability, which can cause power outages and blackouts and lower industry production. The intelligent control mechanism is critical to the PS's operation to ensure frequency under its complicated structure. This study suggests a new best 3-DoF fractional order proportional integral derivative-model predictive controller (3DoF-FOPIDN-MPC) for controlling frequency when there is a lot of load going on quickly. The 3DoF-FOPID controls the outer loop using the area control error (ACE) signal, while MPC controls the inner loop using the output signal from the 3DoF-FOPIDN and the area's total power output response. For optimal controller functionality, the salp swarm algorithm (SSA) extracts optimized controller settings. To validate the suggested controller, it is tested under various load-changing scenarios and compared to state-of-the-art controllers. For 1 % and 3 % load changes, the suggested controller settles in 1.1 s and 1.78 s, respectively.

Changes in the equilibrium of the urban transport system of a large city following an urban flood

Urban floods are among the most frequent and destructive natural disasters. They generate enormous economic and non-economic losses, including damage to buildings and transportation infrastructure, which are critical systems supporting community well-being. The purpose of this paper was to assess the impact an urban flood would have on the urban road transport system in Łódź and to determine changes in potential accessibility that would accompany a flood. This paper introduces a novel approach in terms of combining the modelling of direct impact ranges of urban flooding in the area of Łódź and a macroscopic multi-motivational traffic model for the city (using PTV Visum software). This made it possible to identify mechanisms of changes made in as many intra-system relationships as possible, as well as between the system and its surroundings. The results showed that changes in the spatial distribution of traffic volume in the city are closely dependent on the water level. The sections of the network most affected by the load changes are those that form the framework for the entire system of Łódź, indicating a lack of resilience of the car transport subsystem in the critical segment for the functioning quality of the entire subsystem. Additionally, the study was conducted for public transport, and it was indicated that changes in its utilization are minimal. It was also found that the greatest impact on transport accessibility from an urban flood is for ultra-short trips. This is primarily due to the base effect (the initial quality of the infrastructure and its potential) – the internal potential of the transport area deteriorates drastically during a flood, severely affecting accessibility.

Monitoring of thick-walled pressure elements to determine transient temperature and stress distributions using the measured fluid's pressure and wall's temperature

The paper presents a new stress monitoring method for cylindrical pressure elements of the power unit. It can be used to monitor a power unit's start-up, shutdown, and load change to reduce the unit's connection time to the power grid. The outer surface of the component is thermally insulated. Circumferential thermal stress at the point of its concentration at the hole edge is determined based on the stress determined at a greater distance from the hole. The circumferential thermal and pressure stresses at the hole edge are calculated by multiplying the stress values determined for the non-weakened wall by the respective concentration factors. In addition, the heat transfer coefficient (HTC) at the inner surface of the pressure element is necessary to determine the thermal stress concentration factor. Heat transfer correlations available in the literature are used to calculate HTC. The transient element wall temperature is measured five to 12 mm from the inner surface of the cylindrical component. An analysis of the measurement point locations on the accuracy of temperature and stress determining at the inner component surface was investigated. A practical application of the proposed method using real measurement data is presented.

Design and Experimental Testing of Extended-Range Power Supply System for 15 Horsepower Electric Tractor

Electric tractors have many advantages, including high torque, excellent controllability, energy efficiency, a simple structure, and an electric interface for expansion. However, a significant limitation lies in their endurance. This study presents the design of an extended-range power supply system to ensure continuous endurance for an electric tractor. The objective is to provide a continuous power source for our self-developed electric tractor while preserving the benefits of electric propulsion. Extended-range power systems utilize a primary mover, typically an oil-fueled internal combustion engine, to drive the generator for electricity generation, and the generated AC-form electricity is subsequently converted into stable DC bus voltage by a power electronic converter. The hardware and control design of an extended-range power supply system are finalized and validated through experimental trials. The results demonstrate the system’s capability to sustain stable DC bus voltage amidst disruptions such as sudden load shifts and fluctuations in the prime mover’s speed. Even with a 50% sudden load change, the voltage drop is within 12% and can recover to ±3% within 4 s. The extended-range can be used alone without a battery to power the electric tractor, or it can used in parallel with other extended ranges or batteries for power sharing thanks to the droop control ability.

A wide-output buck DC-DC power management IC

-This article designs and develops a wide-input voltage, high-efficiency, small-size, and peak current-mode control step-down DC-DC converter. The Cadence Spectre simulation tool is used for system simulation to verify the performance of the chip. The overall research content of the article includes the function of the output under heavy load, light load and the stability of the output under transient load changes. The specific content of the research is buck synchronous step-down DC-DC converter chip with pulse modulated. It is provided with an input-voltage range of 6 V–80 V and maximum output-voltage range 72 V. The chip possesses wide operating temperature range of −20 °C to 130 °C. The 92 % high-efficiency can be achieved by using a PWM/PFM hybrid modulation method. When achieving transient load jump, the output voltage change shall not exceed 150 mV. The maximum load current of the chip is 1 A. Furthermore, the chip is packaged and samples can be obtained, and the output light load/heavy load, and other functions are tested through the circuit board. In addition, the chip achieved tape out by using 0.18 μm CMOS process with size of 2027 μm × 2020 μm. The converter features current mode control to simplify external compensation and optimize transient response through a wide range of inductors and output capacitors. It can be adopted user-programmable soft-start time to prevent inrush current during startup. It also includes thermal shutdown protection to provide safe and smooth operation in operating conditions.