An effective energy management strategy in hybrid electric vehicles using Taguchi based approach for improved performance

The key challenge in the innovation of hybrid electric vehicles is the energy management control strategies to split the energy between the sources. The objective of adding an auxiliary source of power to vehicles is to minimize battery stress as well as energy consumption rate (ECR) of the main source and to increase the range of the vehicle. Based on Taguchi and grey relational analysis, the optimal control factors were determined for each of the desired performance factors. In this experimental design, control strategy, vehicle model, battery SOC, and UC SOC are considered as control factors, and ECR, range of the vehicle, and battery stress remain as vehicle performance factors. The confirmatory results show the minimal error between the initial set and the optimum factor to be 7.68 for ECR, 8.54 for range, and 5.49 for battery stress, respectively. The results also reveal the importance of fuzzy-based strategy on hybridization of energy storage systems in electric vehicles and also identified the most and the least influencing factors that affect the vehicle performance.Scopu

On Minimizing TCP Traffic Congestion in Vehicular Internet of Things (VIoT)

The performance of end-to-end wireless link congestion control algorithm in the vehicular internet of things network is plagued by the inherent limitations of spurious rate control initiation, slow convergence time, and fairness disparity. In this article, the delay assisted rate tuning (DART) approach is proposed for the vehicular network that implements two algorithms, utilization assisted reduction (UAR) and super linear convergence (SLC), to overcome the transmission control protocol (TCP) limitations. The UAR algorithm is responsible for initiating the proportionate rate control process based on the bottleneck prediction parameter, thereby regulating the needless rate control during non-congested losses. In the congestion recovery mode, the SLC algorithm executes a dynamic rate update mechanism that enhances the flow rate and minimizes bandwidth sharing disparity among TCP flows. An analytical model was developed to study the DART convergence rate and fairness performance against the existing algorithm. The vehicular simulation outcome also confirms significant enhancement in average transmission rate, average message latency, and average bandwidth sharing performances of the DART algorithms against the RFC 6582, TCP-LoRaD, and CERL + congestion avoidance algorithms under varying traffic flows and node movement scenarios

Performance investigation of 140 kW grid connected solar PV system installed in southern region of India-A detailed case study and analysis

This article focuses on the performance assessment of a grid-connected 140-kW photovoltaic (PV) plant which is installed on the roof of an aerospace hanger block located at the SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India. The installed unit comprises of seven parallel strings, each comprised of 60 modules. Each of the seven strings is separately connected to an individual inverter (Delta RPI-M20A), i.e., a string inverter of 20 kW. An investigation deals with parameters recorded based on the average of daily, monthly, and yearly data such as AC and DC energy generated, reference yield, array yield and final yields, performance ratio and capacity factor. In the year 2020, the total power generated by the proposed project site is 139,125 kW. Further, the average reference yield varied from a minimum of 118.9 (hr/mth) to a maximum of 197.6 (hr/mth). Similarly, the average final yield varies from 86.14 (hr) to 135.61 (hr). The capacity factor and performance ratio are found to have a maximum of 18.83% and 80.29% and a minimum of 11.96% and 64.14%, respectively. Thus, this article helps readers identify the practicability and sustainability of solar-powered PV systems in rural and remote locations.The authors would like to thank the SRM Institute of Science and Technology, Kattankulathur campus for supporting this research work.Scopu

Performance analysis and enhancement of brain emotion-based intelligent controller and its impact on PMBLDC motor drive for electric vehicle applications

Growing awareness of electric vehicles insists on the necessity of Permanent Magnet Brushless Direct Current Motor (PMBLDCM) worldwide. This paper involves building a simulation model of the complete PMBLDCM drive system using Matlab/Simulink to control the speed and Torque. Using the Simulink model, speed parameters with various controllers of the drive system are studied and analyzed. The conventional PI controller is capable of controlling the speed of the PMBLDC motor. H1owever, it cannot give assurance of the stability of the motor throughout the load variation. In a speed loop, Improved Brain Emotional Learning Based Intelligent Controller (IBELBIC) is proposed in this paper. The proposed IBELBIC-based PMBLDC motor drive system with a rating of 3 phase, 30 V, 400 W, 3000 RPM is implemented using Spartan 3 Field Programmable Gate Array (FPGA) from Xilinx. This paper presents an IBELBIC design for enhancing the speed performance of the drive system at various set speeds and different load conditions of 1.2 Nm load, 0.6 Nm load, and no load. The proposed PMBLDCM drive system is realized with the help of a Very high speed integrated circuit Hardware Description Language (VHDL) programming algorithm of digital Pulse Width Modulation (PWM) generator topology. Various test cases are evaluated under different operating conditions to demonstrate the learning capability and the applicability of the proposed controller. In this paper, simulation validation is done using hardware setup, and experimental results are monitored on a computer using a customized program developed using LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench). Instead of a Data Acquisition (DAQ) card, the Virtual Instrument Software Architecture (VISA) tool of LabVIEW software is used in this work and results in cost minimization of the experimental setup.Scopu

A simplified methodology for renewable energy integration and harmonic current reduction in hybrid micro grid

Due to advancements in power electronics devices and the support of improvements on both the power supply and load sides, Distributed Energy (DG) is rapidly being connected to the grid in the form of AC/DC Hybrid Micro-Grid (HMG). The development will result in a substantial change in the network topology, new design problems for the micro-grid control unit, and new requirements for the simulation testing laboratory. The Bidirectional AC-DC converter (BAC) is necessary for hybrid microgrids to provide voltage stableness and power equilibrium between the AC and DC grids. To suppress the harmonic current control approach, an enhanced Fryze-Buchholz Depenbrock (FBD) current harmonic detection technique is integrated with droop control in this paper. This proposed system not only performs the power transformation but also minimizes harmonics. While considering non-linear load, the proposed system yields the control ability for regulating the converter to eliminate the harmonics of 74.41% in the grid current. While incorporating the HMG in the proposed system, the control strategy decreases 90.3% and 89.4% of reactive power in both linear and non-linear loads. The obtained simulation results are used to confirm the feasibility and effectiveness of the control scheme.Scopu