Half Load Research Articles

Experimental study and statistical analysis of system performance parameters of a household freezer

The present research comprehensively examines the influences of different input variables, such as cabinet load level, ambient temperature, relative humidity, door opening time and day, on the output parameters of frosting amount, recovery time, and total energy consumption of the upright domestic freezer following the door opening operation. Moreover, a holistic statistical methodology, which is known as the GLM-ANOVA, was implemented for determining the parametric experimental results. Meanwhile, the effects of binary interactions between the input factors on the output parameters were extensively evaluated using statistical methods. As a consequence, the amount of frost increases with an upward gradient as the load level within the cabinet escalates from 25 °C to 32 °C. Both the duration of door openings and the relative humidity level have a double impact on the frosting. Moreover, the duration required for the system to recover from half load to full load more than doubles with an increase in ambient temperature from 25 °C to 32 °C. On the other hand, at an outdoor temperature of 25 °C, the recovery time demonstrates a close to linear relationship with the load level of the cabinet. Furthermore, the duration of door openings and the load capacity within the cabinet are considered two important factors that simultaneously influence the daily energy consumption. The infiltration of ambient air into the freezer compartment and the presence of moisture in the air substantially increase the energy consumption, especially when the relative humidity fluctuates between 30 % and 65 % and the door opening duration stretches from 10 to 20 s, respectively.

A new hybrid control strategy for improving ride comfort on lateral suspension system of railway vehicle

The ride comfort is a key research area for the quality improvement of railway vehicles. Several control methods have been developed to improve the ride comfort, in which the semi-active control approach inherits the advantages of passive and active control approaches. However, the semi-active control may perform ineffectively in vibration attenuation when the carbody load changes. To address this issue, we proposed a novel hybrid control method that combines the skyhook (SH) and displacement velocity (DV) control methods to reduce vibrations of the carbody in the lateral direction under carbody load changes. First, a hybrid control model built in Matlab software was applied to a quarter railway vehicle model for a preliminary assessment of the ride comfort. Second, to provide a more comprehensive evaluation, the proposed model was applied to a whole railway vehicle model using co-simulation (Matlab-Simpack). In the quarter model, under the sinusoidal excitation, the hybrid control showed a lower acceleration by 48.5% and 42.8% when the carbody load reduced to a half and a quarter, respectively, compared to the passive control. This finding was confirmed with the whole model. Moreover, in the whole model, under the track irregular excitation, the hybrid control showed a lower acceleration by 26.6% and 17.4% when the carbody load reduced to a half and a quarter, respectively. Further, the proposed method showed an acceptable safety level, measured by the derailment coefficient (0.0743 at a half load and 0.089 at a quarter load). In conclusions, the proposed hybrid SH-DV control exhibits high robustness, adaptability, effectiveness, and acceptable safety level in response to variations in body load.

Analysis of Scalable Resonant DC–DC Converter Using GaN Switches for xEV Charging Stations

In this research, an innovative electric vehicle (EV) charger is designed and presented for xEV charging stations. The key feature of our system is a scalable, interleaved inductor–inductor–capacitor (iL2C) DC-DC converter operation. The proposed system employs two parallel L2C converters with 8-GaN switches on the primary side and a shared rectifier circuit on the secondary side. This configuration not only amplifies the resonant tank internal currents and losses generated by the switches but also improves current sharing. A novel closed-loop technique is proposed with a constant-voltage method of operation, along with a hybrid control scheme of variable frequency + phase shift modulation (VFPSM). To examine the controller and converter’s performance, an experimental demonstration is conducted under varying load conditions, including full load, half load, and light load, where the source voltage and load voltage are maintained at constant levels of 400 Vin and 48 V0, respectively. Furthermore, line regulation is conducted and verified to accommodate a broad input voltage range of 300 Vin–500 Vin and 500 Vin–300 Vin while maintaining an output voltage of 48 V0 at 3.3 kW, 1.65 kW, and 0.33 kW with a peak efficiency of 98.2%.

Multi-Objective Optimization Strategy for Fuel Cell Hybrid Electric Trucks Based on Driving Patern Recognition

Fuel cell hybrid electric trucks have become a cutting-edge field in understanding urban traffic emissions due to their enormous potential in low-carbon areas. In order to improve the economy of fuel cell hybrid electric trucks and reduce the decline of fuel cell lifespan, this paper proposes a multi-objective energy management strategy that optimizes weight coefficients. On the basis of establishing a fuel cell battery hybrid system model, three modes of uniform speed, acceleration, and deceleration were identified through clustering analysis of vehicle speed. Reinforcement learning algorithms were used to learn the corresponding weights for different modes, which reduced the decline in fuel cell life while improving the economic efficiency. The simulation results indicate that, under the conditions of no load, half load, and full load, the truck only sacrificed 0.9–5.6%, 1.7–2.6%, and 1.2–1.6% SOC, saving 5.7–6.45%, 5.9–6.67%, and 6.1–6.67% in lifespan loss, and reducing hydrogen consumption by 3.0–7.1%, 2.8–4.4%, and 1.0–3.0%, respectively.

Impact on Long Duration of Overvoltage Due to Back-Feed Restoration of Distribution Network

In power system, power outages can be critical; if the environment and public safety within risk situation. Therefore, restoration power is needed to respond on system distribution to reduce the power restoration time and making the system reliable and efficient. Backfeeding using a nearby feeder in a power system is proposed in this research. When a power outage occurred, the faulted area is isolated from the system and searching available nearby feeders that can restore the outage area without any violation. However, analysing the effects of using a nearby feeder for back feeding is needed to avoid voltage violations. This paper analyses the voltage during the healthy and faulted condition, the impact of using a nearby feeder for backfeeding for a full load, half load and during no-load conditions are examine and also determine the maximum increment limitation of a load during back-feed if a qualified feeder is selected. Newton Raphson method is applied to calculate the power flow in the system and observe the stability of backfeed configuration. The results show the highest voltage supply occur during no load followed by half load and lastly during full load. The maximum voltage increment of load on backfeed is determined to be 0.95pu as an ideal voltage value.

Coupled inductor‐based buck power factor correction (PFC) converter with soft switching

SummaryIn this study, couple inductor‐based buck power factor correction (PFC) converter is designed to mitigate dead zones of the converter. To minimize switching losses, all switches are controlled using a soft switching method, eliminating the need for snubber circuits. The circuit is controlled by an analog UC3843 pulse width modulation (PWM) integrated circuit (IC), providing natural PFC capability, which simplifies control and offers advantages in terms of size and cost compared to conventional ones. Simulation studies and prototype implementation are carried out to evaluate performance of the topology. The converter operates within a voltage range of 90–280 Vrms and has a power rating of 150 W. The results from both simulation and experimental analyses indicate that power factor (PF) of the circuit exceeds 98% and total harmonic distortion (THD) of the input current is found to be below 5% under various input voltage and load conditions. Furthermore, proposed topology demonstrated high efficiency, with measurements of 93% at full load and 95.6% at half load under 220 Vrms input voltage and 80 Vdc output voltage conditions. Outcomes highlight that the proposed topology achieves pure sinusoidal input current and exhibits competitive performance compared to other topologies used in the industry.

Simulation Study on Dynamic Characteristics of the Chain Drive System for Mining Scraper Conveyor Driven by the Permanent Magnet Synchronous Motor

The chain drive system represents a critical subsystem within the scraper conveyor. This paper proposes a joint simulation model for the drive system of the scraper conveyor, driven by the permanent magnet synchronous motor, in order to conduct a comprehensive analysis of the dynamic characteristics of the chain drive system during the operational process. Firstly, the dynamic simulation model for the mining scraper conveyor’s chain drive system was established in ADAMS, taking into account its structural characteristics. Then, the mathematical model of the permanent magnet synchronous motor was established using the coordinate transformation theory, and the speed controller based on vector control was designed by using the theory related to sliding mode control. The coupling relationship between the chain drive system of the scraper conveyor and the permanent magnet synchronous motor drive system was investigated. Finally, a joint simulation model of the mechanical system and motor control system was created using ADAMS (View 2019) and MATLAB/Simulink (2020a). The dynamic characteristics of the chain drive system were analyzed, and the three typical working conditions of no load, half load, and rated load were considered. The results show that the contact force between the flat ring and the sprocket undergoes an initial increase, followed by a decrease, and finally another increase. As the load increases from no load to full load, there is a marked increase in the contact force between the loaded side chainrings. Due to the polygon effect, both the speed curve of the permanent magnet drive motor and the contact force curve between the ring chains exhibit periodic fluctuations. The research in this paper provides an idea for the coupling analysis of the scraper conveyor electromechanical system.

Enhancement of Efficiency and Mitigation of Pollutan Emissions in a Compression Ignition Engine by the Utilization of Rice Bran Oil as Green Fuel

The current investigation involved the implementation of a research experiment aimed at assessing the operational and emission attributes of a compression ignition direct injection engine comprising a single cylinder. The engine was fuelled with rice bran oil (RBO), and its performance was analysed under different engine loads. The performance metrics that were analysed included the brake specific fuel consumption BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), and cylinder pressure. The exhaust emission parameters that were investigated include carbon monoxide (CO), carbon dioxide (CO2), hydrocarbons (HC), and oxide of nitrogen (NOX). The study compares the results obtained from an experimental investigation involving different variants of rice bran oil (RBO50, RBO75, RBO100) with those obtained from a diesel engine (RBO00). The lowest BSFC obtained for RBO100 is around 0.29 kg/kWh at maximum load conditions (75 %), while the highest obtained for RBO00 is 0.33 kg/kWh. For all operations of diesel and RBO blends, it was discovered experimentally that the BSFC increases until 25 % of engine load and then starts to decline as the engine load is raised. At normal engine load circumstances, RBO75 has the highest thermal efficiency, while RBO00 has the lowest. The high EGT reading of RBO50 blends was due to the high calorific value (CV) of the fuel blends, which produced more heat per unit mass than RBO75 and RBO100. RBO75 achieved the highest cylinder pressure under both half and full load scenarios. RBO00 (pure diesel) achieved the lowest cylinder pressure under both half and full load scenarios. RBO outscored diesel in terms of efficiency of engine. The exhaust emission characteristics that were assessed included NOX, CO2, HC, and CO. The experimental outcomes of the study using rice bran oil-based fuels, specifically RBO50, RBO75, and RBO100, are being contrasted with those of diesel fuel (RBO00). The findings indicate that emissions of CO, CO2, HC, and NOX are lower when using RBO75 and RBO100 compared to diesel fuel. Furthermore, an analysis was conducted to determine the HC emissions of both RBO75 and RBO100 fuels at two distinct engine speeds, specifically 3500 rpm and 2000 rpm. The HC emission level for RBO75 was observed to be at its peak of 211 ppm when the engine speed reached 3500 rpm. The RBO50 fuel exhibits lower levels of CO emissions, measuring at 1.2% (3500 rpm) and 0.32% (2000 rpm). Similarly, CO2 emissions are also reduced with RBO50, measuring at 8.3% (3500 rpm) and 6.9% (2000 rpm). These exhaust emission reductions are observed when comparing RBO50 to diesel (RBO00) and other fuel mixtures, under a 75% load condition. Elevated levels of NOX emissions were detected in diesel fuel (RBO00) at concentrations of 499 ppm (3500 rpm) and 599 ppm (2000 rpm). In comparison to other fuels such as RBO50, RBO75, and RBO100, these higher NOX emissions were noted. In summary, the emission properties of RBO were shown to be superior to those of diesel fuel. The optimal blend for emissions reduction, including CO2, CO, NOX, and HC, was determined to be RBO50.

Engine performance and emission characteristics of microwave-produced biodiesel blends

The main objective of this research is to investigate, experimentally, the effects of biodiesel blends on the performance and emissions of a Diesel engine. Measurements were carried out on a single-cylinder, four-stroke, and air-cooled compression-ignition engine, under half and full load conditions. Engine speed was varied from 1000-3000 rpm. Biodiesel was produced by transesterification process of sunflower oil with ethanol, using microwave-assisted heating reactor. Three biodiesel-diesel mixtures: containing 5%, 10%, and 20% by volume of biodiesel, respectively, have been tested and compared to pure diesel fuel. The effects of these biodiesel blends on the engine operating characteristics such as brake specific fuel consumption, brake power, brake thermal efficiency, brake mean effective pressure, and on carbon CO, CO2, and NOx emissions, have been investigated. It was noticed that, at full load, the specific fuel consumptions of biodiesel blends were higher compared to the pure diesel fuel, but no change was observed under ? load. An improvement in the brake thermal efficiency, under ? load, was obtained, but at full load, for medium and high speed, the thermal efficiencies of all biodiesel blends showed a decrease compared to pure diesel fuel. Concerning pollutants emissions, a decrease in CO emissions of all biodiesel blends was noticed. The best result in CO emissions was achieved by the mixture containing 10% by volume of biodiesel with an average reduction value close to 40%. In addition, a significant reduction in NOx emissions was observed for the three biodiesel blends.

Optimizing dialysis water treatment based on medical planning requirements

This paper introduces a new approach to improving hemodialysis and peritoneal dialysis processes. This maintains compatibility between the water treatment unit and active dialysis machines. Identification of different deviations in the patient’s requirements to classify the suitable flow rate (FR) of the pure water can be created through an Adaptive Neuro-Fuzzy Inference System (ANFIS). Four types of categories are classified: quarter load, half load, three-quarter load, and full load. This includes two main steps: identifying the dialysis categories with patients and measuring the suitable FR for each category. The effective FR of water was computed to indicate how the number of pumps rose as the number of patients treated within the dialysis unit increased. The introduced prediction method was tested against artificial neural networks to predict alum doses (ANN-AD) method, artificial intelligence as a combinatorial optimization strategy (AN-COS) using peach-palm waste in a solid-state fermentation environment, expert system applications (ESA) in chronic kidney disease management (MDSSs), prescription optimization for automated peritoneal dialysis (BCPH). In this work, pumping system parameter estimation was utilized to assess the performance of the introduced systems based on input voltage, input current, rotor speed, and electromagnetic torque waveforms of the pumping drive. This method uses the ANFIS algorithm to construct a high-performance pumping system to evaluate and predict the flow rate of dialysis machines based on input–output estimates. The flow rate values for each patient in critical care units can be controlled by the presented algorithm according to the time of dialysis. A good predictive model based on integrating the experience and decision making of medical planners was implemented. The proposed method not only improves accuracy but also saves time in the dialysis unit. The presented fuzzy classifier uses the ratio of the number of predicted true positives and false positives to the total number of anticipated positives. The simulation results show that the proposed technique can be successfully used to classify the suitable FR of the water according to the hemodialysis load. One of the advantages of the presented technique is the ability to predict the value of FR in real time with reliability, low computational complexity, and a high accuracy of 98.01%, which simplifies the dialysis process for many patients while at the same time leading to improved performance of hemodialysis. The presented method can be implanted in online FR estimation and analysis hardware for hemodialysis, is easy to calculate and run in real time, minimizes hemodialysis costs, and saves run time.

An industrial design of 400 V – 48 V, 98.2% peak efficient charger using E‐mode GaN technology with wide operating ranges for xEV applications

AbstractThis paper offers a wide‐operating range electric vehicle charger design by employing an interleaved inductor–inductor–capacitor iL2C DC–DC converter. It uses two parallel L2C converters with 8‐GaN switches on the primary side and a shared rectifier circuit on the secondary side, which it also enhances the circulating current, conduction losses, and current sharing. For iL2C converter, a constant voltage charging mode of operation is designed, also it proposes a hybrid control scheme of variable frequency + phase shift modulation (VFPSM). The entire concept is designed, simulated, and validated with a rated input voltage and load voltage of three different load conditions with converter line and load regulations are analyzed. To evaluate controller and converter performance, the idea is proven experimentally for variable load condition of full load, half load, light load with a rated input and output voltage of 400 Vin–48 V0. In addition, line regulation is also performed and validated for wide input voltage application of 300 Vin–500 Vin with an output voltage of 48 V0 at full load and peak efficiency of 98.2% is determined. Further, to provide the system effectiveness converter efficiencies are presented at various load operations from 3.3 kW to 330 W.

Sloshing Response of an Aquaculture Vessel: An Experimental Study

The sloshing response is crucial to the design and operation of aquaculture vessels and affects the safety of the culture equipment and the efficiency of the culture operation. A 1/50 scaled model was utilized to investigate the coupled sloshing response characteristics of a novel aquaculture vessel in a wave basin. Two wave directions (beam and head wave) and two filling levels (81.5% and 47.4%) are taken into account. The time-domain and frequency-domain characteristics of the sloshing response under the linear regular wave and extreme operational sea state were investigated using regular wave tests and irregular wave tests, respectively. The sloshing mechanism in the aquaculture tanks is complicated, due to the coupling effect between external waves, ship motion, and internal sloshing. In linear regular waves, the wave frequency mode dominates the sloshing response, which is larger under beam wave conditions than under head wave conditions and larger under half load conditions than full load conditions. The irregular wave test results confirmed the regular wave test conclusions, but the sloshing response has stronger nonlinearity, higher natural modes appeared, and the amplitude of the higher natural modes is also relatively larger.

A cyclic GTN model for ultra-low cycle fatigue analysis of structural steels

Ultra-low cycle fatigue (ULCF) is a critical concern in the seismic design of steel structures due to its adverse effects on the ductility and energy dissipation capacity of steel connections. The Gurson-Tvergaard-Needleman (GTN) model, a well-accepted micromechanical fracture model, cannot be applied directly to ULCF analysis, as it requires proper estimation of the effects of cyclic loadings on the ductile fracture of materials. In this paper, a cyclic GTN (C-GTN) model was proposed for the ULCF prediction of materials, in which the evolution of microvoids during ULCF loadings was addressed for tensile and compressive half load cycles, respectively, and the effect of the cumulative plastic strains on the material’s resistance to ductile fracture was considered by the reduction of the critical void volume fraction for void coalescence. Then, a VUMAT subroutine was programmed for the C-GTN model, in which the cyclic hardening behavior of materials was simulated with the Voce-Chaboche model. Finally, the C-GTN model was calibrated for the G20Mn5QT cast steel based on previous tests on notched round bar specimens of the material. The applicability of the C-GTN model and the VUMAT subroutine were validated in the ULCF analysis of double-hole plate specimens of the G20Mn5QT cast steel.

Design and research of a novel solid oxide fuel cell with thermal energy storage for load tracking

Solid oxide fuel cell (SOFC) is a promising energy conversion device. However, the severe temperature fluctuations and slow load switching caused by huge thermal inertia during load tracking are urgent issues to be solved. In this paper, a novel SOFC system with thermal energy storage (TES) was proposed and studied. The 1D models of fuel cell stack and TES were established based on electrochemical and thermodynamic laws. The output power switch between full load and half load was explored as an example, and the dynamic response of the proposed system and traditional SOFC was compared, which was achieved by step changes in current. The results indicated that the maximum fluctuations in the inlet gas temperature of traditional SOFC stacks under load step-down and step-up conditions were 169.21 K and 95.24 K, respectively. TES could maintain a constant gas temperature at the entrance of fuel cell stack, thereby avoiding severe temperature fluctuations in the stack. The proposed system would significantly reduce the maximum temperature gradient during load switching and half-load operation. In addition, compared to traditional SOFCs, the dynamic response time of the system with TES had been reduced from thousands of seconds to around 300 s, which meant that the load step-down and step-up processes had been shortened by 93.79 % and 80.52 %, respectively. The response time of load step-down was longer than that of step-up, due to heat generation within the fuel cell stack. The output power of the proposed system during half load operation was 0.21 KW higher than traditional system, which meant an increase of 7.75 % in output power. Finally, the ramp current was adopted to solve the problem of fuel definition in step-up condition, and the response time of the power was 41 s longer than the step current.

A Novel Hybrid Control Strategy and Dynamic Performance Enhancement of a 3.3 kW GaN–HEMT-Based iL2C Resonant Full-Bridge DC–DC Power Converter Methodology for Electric Vehicle Charging Systems

The conventional resonant inductor–inductor–capacitor (L2C) DC–DC converters have the major drawbacks of poor regulation, improper current sharing, load current ripples, conduction losses, and limiting the power levels to operate at higher loads for electric vehicle (EV) charging systems. To address the issues of the L2C converter, this paper proposes an interleaved inductor–inductor–capacitor (iL2C) full-bridge (FB) DC–DC converter as an EV charger with wide input voltage conditions. It comprises two L2C converters operating in parallel on the primary side with 8-GaN switches and maintains the single rectifier circuit on the secondary side as common. Further, it introduces the hybrid control strategy called variable frequency + phase shift modulation (VFPSM) technique for iL2C with a constant voltage charging mode operation. The design requirements, modeling, dynamic responses, and operation of an iL2C converter with a controller are discussed. The analysis of the proposed concept designed and simulated with an input voltage of 400 Vin at a load voltage of 48 V0 presented at different load conditions, i.e., full load (3.3 kW), half load (1.65 kW), and light load (330 W). The dynamic performances of the converter during line and load regulations are presented at assorted input voltages. In addition, to analyze the controller and converter performance, the concept was validated experimentally for wide input voltage applications of 300–500 Vin with a desired output of 48 V0 at full load condition, i.e., 3.3 kW and the practical efficiency of the iL2C converter was 98.2% at full load.

Application of artificial intelligence and communication technology to water and energy balance models

Abstract The precise correction of water and energy balance is a significant difficulty in studying turbulence energy balance and water flow for agricultural purposes. The need for efficient water and energy management is growing as the world struggles to keep up with rising water and energy demands. This research examines artificial intelligence (AI)'s impact on the water flow and energy balance confluence subnetwork of sensing elements from all the original network's nodes. The study proposed an AI-based optimized sensor energy balance model (AI-SEBM) that uses pressure data to maintain energy balance in turbines and save water with the optimized energy source for agriculture usage. This research explores the potential for installing Kalpan hydraulic turbines, which are most effective during half-load operation, and to forecast all loads with little computing effort to balance energy in turbulence. To anticipate daily pressure readings and energy consumption across all nodes in the network, an AI-based optimization wireless sensor network is designed for communication and linked to an energy balance system. Sensors are strategically deployed at the network's nerve centres. The maximum flow algorithm is used for a grid representing the water and energy balance to determine the positions of the virtual nodes.

Regression Model-Based Short-Term Load Forecasting for Load Despatch Centre

Forecasting load is an integral part of the planning, operation, and control of power systems. This paper is part of a research effort aimed at developing better energy demand forecasting models for load dispatch centers (LDCs) in Indian states as part of an ambitious project utilizing artificial intelligence-based load forecasting models. In this paper, we present a half hourly load forecasting method for the energy management system of the project that will be used at 33 /11 kV and 0.415 kV substations with good accuracy. The paper uses the half-hourly load consumption dataset collected from MSEDCL for Maharashtra from July 1, 2020 through August 31, 2022. This paper evaluates 24 regression model-based half hourly based load forecasting algorithms for ALE PHATA load based on the load consumption dataset and the collected meteorological dataset. The 24 models in MATLAB Regression belong to five types of regression models: Linear Regression, Regression Trees, Support Vector Machines (SVM), Gaussian Process Regression (GPR), Ensemble of Trees, and Neural Networks. As a consequence of their nonparametric kernel-based probabilistic nature, the GPR family of models demonstrates the best load forecasting performance. Least squares estimation was used to determine the regression coefficients. There is a direct correlation between load in an electrical power system and temperature, due point, and seasons, as well as a correlation between load and previous load consumption. Therefore, the input variables are Wet Bulb Temperature at 2 Meters (C), Dew/Frost Point at 2 Meters (C), Temperature at 2 Meters (C), Relative Humidity at 2 Meters (%), Specific Humidity at 2 Meters (g/kg) and Wind Speed at 10 Meters (m/s). The mean absolute percentage error and the R squared are used to validate or verify the accuracy of the model, which is shown in the results section. Based on this study, two GPR models are recommended for load forecasting, the Rational Quadratic GPR and the Exponential GPR and Exponential GPR as final model.

Improving ride comfort and road friendliness of heavy truck using semi-active suspension system

To enhance the ride comfort and improve the road friendliness of the heavy truck, based on the dynamic model of the heavy truck, the semi-active suspension system of the vehicle is proposed and controlled based on the fuzzy logic control and Matlab/Simulink software. The efficiency of the semi-active suspension system is then evaluated based on the indexes of the root mean square acceleration of the driver’s seat, the root mean square acceleration of the cab's pitching angle, and the dynamic load coefficient of the wheel axles. The results show that with the semi-active suspension system of the heavy truck controlled by the fuzzy logic control, the acceleration responses of the heavy truck and the dynamic forces of the wheel axles are greatly reduced in comparison with the passive suspension system under various operating conditions of the loads and speeds. Especially, with the semi-active suspension system controlled by the fuzzy logic control, the root mean square accelerations of the driver’s seat and cab pitch angle; and the dynamic load coefficient at 2nd axle of the wheel are clearly reduced by 23.7 %, 27.2 %, and 20.9 % in comparison with the passive suspension system, respectively. Thus, both ride comfort and road friendliness of the heavy truck are improved by the semi-active suspension system. In addition, the vehicle load insignificantly affects ride comfort. However, it greatly affects the road damage, especially with the half load condition of the vehicle. Thus, to improve road friendliness, the full load condition of the vehicle should be used.

Design of a Dynamic Hybrid Compensator for Current Sharing Control of Parallel Phase-Shifted Full-Bridge Converter

The phase-shifted full-bridge (PSFB) converter has been widely used in power supply modules due to its simple control and high output power. However, with the market’s increasing demand for higher power sources, the PSFB converter needs to face challenges in increasing its output power level. Compared to redesigning a larger power module or a larger single converter, it will be more cost-effective to achieve a higher power output by paralleling the existing converters. However, due to the manufacturing differences in circuit components, the output imbalance in parallel PSFB converter systems may damage the power modules. Thus, the influence of differences in circuit components is analyzed in this paper, and it is found that the leakage inductance and transformer ratio are the main factors resulting in errors in current sharing control. Consequently, a dynamic hybrid compensator (DHC) is proposed in this paper, that can significantly reduce the error in current sharing control via the compensation of the duty cycle of a slave module. Furthermore, the DHC is verified on an 800 W two-phase PSFB converter, which shows that even when the difference in components is as large as 20%, the proposed method can still reduce the error in current sharing control to less than 2% under both half and full load conditions.

Combined impact of excess air ratio and injection strategy on performances of a spark-ignition port- plus direct-injection dual-injection gasoline engine at half load

Spark-ignition direct-injection gasoline engine is one of the main power of passenger cars. In this study, combined impact of excess air ratio (λ) and injection strategy on performances of a spark-ignition port- plus direct- injection (PI + DI) dual-injection gasoline engine at half load was investigated experimentally. Experimental results show that the brake mean effective pressure decreased with increasing λ at half load; the brake thermal efficiency first increased, then reached the highest value at approximately λ = 1.1 or 1.2 for different injection strategies, and finally decreased with increasing λ; the maximum cylinder pressure, maximum heat release rate and maximum cylinder temperature decreased with increasing λ, and their corresponding crank angles delayed; the starting of combustion (CA05) increased with increasing λ, the CA05 at PI0DI100 (0 % PI and 100 % DI per cycle), late DI mode and any λ values was the closest to top dead center; for early DI mode, combustion center (CA50) of PI0DI100 was greater or lower than that of PI50DI50 (50 % PI and 50 % DI per cycle) at roughly λ < 1.15 or λ > 1.15, respectively; combustion stability (COVimep) of early DI mode can be controlled within 2 %; the λ had a significant effect on brake-specific carbon monoxide (BSCO) emission at rich mixture and a little effect on BSCO emission at lean mixture; the brake-specific hydrocarbon (BSHC) emission of early DI mode was much higher than that of late DI mode, the injection strategy had an important effect on HC (hydrocarbon) emission; for early DI mode, the brake-specific nitrogen oxides (BSNOX) emissions first increased with increasing λ, then reached the highest value at λ = 1.1, and finally rapidly decreased with further increasing λ; for late DI mode, the BSNOX emissions decreased with increasing λ; the soot emission decreased with increasing λ; the soot emission of late DI mode was much higher than that of early DI mode; at a constant λ, sootPI50DI50,early DI mode ≈ sootPI0DI100, early DI mode ≪ sootPI50DI100, late DI mode < sootPI0DI100, late DI mode.