Browsing by Author "Singh, Dheerendra"

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Analysis of temperature sensitive electrical performance of sputter grown Ni and Ni–Cr Schottky contacts on 4 H-SiC
(Springer, 2024-11) Singh, Dheerendra; Mourya, Satyendra Kumar; Bhatt, Upendra Mohan
This paper studies the temperature-dependent electrical transport properties of nickel (Ni) and nickel–chromium (Ni–Cr) sputtered on n-type 4 H-SiC substrate. Barrier inhomogeneities have been found to affect the electrical parameter of the Schottky barrier diode (SBD) from 323 to 423 K temperature range, We have done current–voltage characterization of Ni and Ni–Cr Schottky junctions. The barrier height , reverse saturation current , ideality factor and series resistance were obtained from I–V characteristics of Ni and Ni–Cr and these parameters are observed to be highly dependent on temperature. It has been observed that Ni–Cr contact has exhibited better electrical characteristics as well as thermal sensitivity as compared to Ni. This may be attributed to the smaller number of barrier inhomogeneities at the Ni–Cr/4 H-SiC interface. In the temperature range from 323 to 423 K, Ni and Ni–Cr-based Schottky contacts, Following observation has been noticed (a). Schottky barrier height (SBH) increased from 1.24 to 1.37 eV and 1.15 to 1.45 eV, (b). Ideality factors reduced from 3.76 to 2.61 and 3.20 to 2.53, (c). Series resistance decreased from 10.22 to 3.37 and 2.45 to 1.16 , and (d). Reverse leakage current to A and to A respectively. The V–T curves for both SBDs are investigated (for the same temperature range) to calculate their thermal sensitivity at and A, respectively. The V–T curves with linear behavior are used to calculate the thermal sensitivity coefficient , which was found to be 7.11 to 7.93 mV/K for the Ni–Cr SBD, and 7.1 to 20.01 mV/K for the Ni/4 H-SiC contacts. The sensitivity-current characteristics for the Ni/4 H-SiC SBD were found to be a non-linear comparison with Ni–Cr/4 H-SiC SBD, which may be attributed to the presence of a highly resistive and non-uniform coating of Ni at the interface.
A Comparative Analysis of Digital and Passive Filters for IFOC based Induction Motor Drive (EV) fed through ZSI
(IOP, 2018) Singh, Dheerendra
It is known that harmonics are generated in any power electronics based application. Since presence of harmonics is not desirable, it is necessary to remove the harmonics. The IFOC is based on stator current regulation, and the stator currents are sensed and used in the speed control algorithm. The current needs to be free from noise and harmonics for accurate further processing. In this paper, a passive analog filter, as well as a 50th order FIR filter is designed in MATLAB and implemented in Code Composer Studio to remove noise and distortion, and a comparative analysis has been done, for the speed control of an induction motor fed through ZSI, for electric vehicle application.
A comprehensive review on hybrid electric vehicles: architectures and components
(Springer, 2019-03) Bansal, Hari Om; Singh, Dheerendra
The rapid consumption of fossil fuel and increased environmental damage caused by it have given a strong impetus to the growth and development of fuel-efficient vehicles. Hybrid electric vehicles (HEVs) have evolved from their inchoate state and are proving to be a promising solution to the serious existential problem posed to the planet earth. Not only do HEVs provide better fuel economy and lower emissions satisfying environmental legislations, but also they dampen the effect of rising fuel prices on consumers. HEVs combine the drive powers of an internal combustion engine and an electrical machine. The main components of HEVs are energy storage system, motor, bidirectional converter and maximum power point trackers (MPPT, in case of solar-powered HEVs). The performance of HEVs greatly depends on these components and its architecture. This paper presents an extensive review on essential components used in HEVs such as their architectures with advantages and disadvantages, choice of bidirectional converter to obtain high efficiency, combining ultracapacitor with battery to extend the battery life, traction motors’ role and their suitability for a particular application. Inclusion of photovoltaic cell in HEVs is a fairly new concept and has been discussed in detail. Various MPPT techniques used for solar-driven HEVs are also discussed in this paper with their suitability.
Control Strategies and Power Decoupling Topologies to Mitigate 2ω-Ripple in Single-Phase Inverters: A Review and Open Challenges
(IEEE, 2020) Singh, Dheerendra; Gautam, Aditya R
This paper provides a comprehensive review of the control approaches and the power-decoupling topologies to mitigate 2ω -ripple problem in the single-phase inverters, its solutions, and discusses open challenges yet to be addressed. The cause and effects of 2ω -ripple problem and its solution based on the passive and active power-decoupling techniques are discussed. A subcategory of the active power-decoupling technique nominated as the control-oriented compensation technique is reviewed in detail, this technique can achieve the ripple-mitigation at the source through the control but not necessarily adds extra circuit or active filter to the system. The control-oriented compensation techniques can be applied in the two-stage DC-DC-AC converters and the single-stage inverters having a front-end control capability with the H-bridge such as in the quasi-switched-boost inverters. The merits and associated challenges of these techniques are listed and summarized in a tabular form. Finally, a conclusive discussion with open challenges is presented
Design of an Improved Q-ZSI with Fault Tolerance for EV Applications
(IEEE, 2019) Bansal, Hari Om; Singh, Dheerendra
In this paper, a Fault Tolerant Quasi Z-source Inverter (Q-ZSI) topology has been proposed for three phase induction motor drive systems. The proposed topology incorporates the ability to detect an open circuit or a short circuit fault in any of the switching arms. Once a fault is detected the firing signal is transferred to another switching arm to ensure uninterrupted flow of power. The main goal of this paper is to design a rugged inverter topology that can give better performance than the standard Z-Source Inverters (ZSI) in harsh environments where the switches are more prone to faults.
Development of a fuzzy-pi tuned bidirectional charger for electric three-wheeler applications
(IEEE, 2025-05) Bansal, Hari Om; Singh, Dheerendra
The growing worldwide market for electric vehicles (EVs) has put pressure on automotive system developers to improve charging efficiency and enhance the charging infrastructure. Bidirectional chargers support the grid by flowing the power in the two directions, i.e. functioning in both V2G and G2V modes. In this paper, a bidirectional converter interfaces a fixed DC bus that supports EV battery charging and discharging operation, is presented and simulated in a MATLAB environment. A Fuzzy Logic tuned Proportional Integral (FLPI) is designed using MATLAB Simulink to enhance the charger's performance. This paper also presents a performance comparative analysis of the FLPI and conventionally used PI Controller, highlighting the FLPI controller's advantages. FLPI is better than the conventional PI because of low errors, faster response time, better transient performance and improved robustness. The charger is developed and simulated for a 600V DC supply with a peak output power of 10kW. The simulation results demonstrate the charging and discharging of a 72V 150 Ah Lithium-ion (Li-ion) battery for electric-3-wheeler applications.
Development of an adaptive neuro-fuzzy inference system–based equivalent consumption minimisation strategy to improve fuel economy in hybrid electric vehicles
(IET, 2020) Bansal, Hari Om; Singh, Dheerendra
The most viable option to achieve the goals of saving energy and protecting the environment is to replace conventional vehicles with hybrid electric vehicles (HEVs). In HEVs, the operational characteristics of an internal combustion engine (ICE) and an electric motor (EM) are different from each other and thus require an adaptive control strategy to achieve higher fuel economy along with smooth operation and better performance of the vehicle. An energy management control strategy is proposed for an HEV based on an adaptive network-based fuzzy inference system (ANFIS). The proposed adaptive equivalent consumption minimisation strategy decides the power to be drawn from ICE and EM based on input parameters such as the speed of the vehicle, the state of charge of the battery, the EM torque and the ICE torque. The whole system is simulated in an advanced vehicle simulator tool. The proposed non-linear controller has also been tested for real-time behaviour using a field-programmable gate array–based MicroLabBox hardware controller to compare its performance against existing controllers. The authors compared the fuel economy obtained using the proposed method with several other methods available in the literature. The comparison clearly reveals that the proposed ANFIS-based method results in better optimization of energy and hence offers better fuel economy. The urban dynamometer driving schedule has been employed for this analysis.
Development of an ANFIS based equivalent consumption minimization strategy to improve fuel economy in Hybrid Electric Vehicles
(IET, 2021-03) Singh, Dheerendra; Bansal, Hari Om
The most viable option to achieve the goals of saving energy and protecting the environment is to replace conventional vehicles with hybrid electric vehicles (HEVs). In HEVs, the operational characteristics of an internal combustion engine (ICE) and an electric motor (EM) are different from each other and thus require an adaptive control strategy to achieve higher fuel economy along with smooth operation and better performance of the vehicle. An energy management control strategy is proposed for an HEV based on an adaptive network-based fuzzy inference system (ANFIS). The proposed adaptive equivalent consumption minimisation strategy decides the power to be drawn from ICE and EM based on input parameters such as the speed of the vehicle, the state of charge of the battery, the EM torque and the ICE torque. The whole system is simulated in an advanced vehicle simulator tool. The proposed non-linear controller has also been tested for real-time behaviour using a field-programmable gate array–based MicroLabBox hardware controller to compare its performance against existing controllers. The authors compared the fuel economy obtained using the proposed method with several other methods available in the literature. The comparison clearly reveals that the proposed ANFIS-based method results in better optimization of energy and hence offers better fuel economy. The urban dynamometer driving schedule has been employed for this analysis.
Digital Implementation of DSVPWM Control for EV fed through Impedance Source Inverter
(IAES, 2015) Singh, Dheerendra
In this paper, a new space vector modulation technique is proposed for speedcontrol of Induction Motor using Z-source inverter powered by a low voltage DCsource. The zero states of conventional space vector modulation is used for boosting the DC link voltage to the required level. The proposed SVM techniqueestimates the required shoot through period of the Z-source inverter to maintainthe DClink voltage constant at the desired level through capacitor voltage control.A 32 bit DSP (TMS320F28335) is used to implement the proposed space vectormodulation method. The power structure and the modulation technique is wellsuited for electric vehicle application.
Edge Computing and Deep Learning Enabled Secure Multitier Network for Internet of Vehicles
(IEEE, 2021-04) Chamola, Vinay; Singh, Dheerendra
Internet of Vehicles (IoVs) are fast becoming the norm in our society, but such a trend also comes with its own set of challenges (e.g., new security and privacy risks due to the expanded attack vectors). In this work, we propose an edge-computing-based secure, efficient, and intelligent multitier heterogeneous IoVs network. We first discuss the functionality and objectives of such an architecture. Then, we demonstrate how unsupervised deep learning techniques can facilitate the identification of suspicious vehicle behavior and ensure the security of such an architecture. The findings from our evaluations demonstrate the learning spatiotemporal information and parameter efficiency of the proposed stacked long short-term memory (LSTM) model over single LSTMs.
Edge Computing and Deep Learning Enabled Secure Multitier Network for Internet of Vehicles
(IEEE, 2021-04) Alladi, Tejasvi; Chamola, Vinay; Singh, Dheerendra
Internet of Vehicles (IoVs) are fast becoming the norm in our society, but such a trend also comes with its own set of challenges (e.g., new security and privacy risks due to the expanded attack vectors). In this work, we propose an edge-computing-based secure, efficient, and intelligent multitier heterogeneous IoVs network. We first discuss the functionality and objectives of such an architecture. Then, we demonstrate how unsupervised deep learning techniques can facilitate the identification of suspicious vehicle behavior and ensure the security of such an architecture. The findings from our evaluations demonstrate the learning spatiotemporal information and parameter efficiency of the proposed stacked long short-term memory (LSTM) model over single LSTMs.
The efficient operating parameter estimation for a simulated plug-in hybrid electric vehicle
(Springer, 2021-10) Singh, Dheerendra; Bansal, Hari Om
Hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs) are indispensable tools in reducing greenhouse gas emissions to fight the twin evils of pollution and climate change. In these vehicles, battery replacement and fuel costs are the major recurring costs over a lifetime. Hence, there is a growing attempt to develop strategies that reduce the long-run expenditure in these vehicles without compromising on performance levels. Further, an increase in the fuel economy is also required for the effective penetration of these vehicles in society. Here, the authors attempt to identify the optimal operating values for battery state of charge (SoC), power ratings of motor, and fuel converter to increase the battery life and fuel economy without degrading the vehicle performance. The simulations have been carried out on Ford C-Max Energi (2016) as a representative for PHEVs based on the Urban Dynamometer Driving Schedule (UDDS) and Highway (HWY) driving cycles. The software used for these simulations is the future automotive systems technology simulator (FASTSim), developed by the National Renewable Energy Laboratory (NREL). In this paper, firstly, the effect of important parameters like battery SoC, fuel converter power, and motor power on HEVs’ driving range, battery life, fuel economy, cost, and charge-depleting range has been analyzed. Based on this analysis, the optimal values of the parameters have been estimated. These parameters have resulted in improvements of driving range by 4.3% and battery life by 18% at a minute cost of a 1% decrease in the charge-sustaining battery life and a 0.4-s increase in the time the car takes to hit 60 mph from the rest. This paper presents a simple, effective, and new approach that explores the effect of altering the existing design parameters on vehicle performance, without manipulating, adding, or deleting any component or controller. This can further be extended to study the impact of various other parameters in the proposed work and opens a way to explore other parameters that exist in various other components of XEVs (where X can be H/PH//F). This study will help in achieving optimal cost reduction in these vehicles.
Electric Power Quality Monitoring (PQM) using Virtual Instrumentation
(IEEE, 2010) Singh, Dheerendra
The paper presents a low-cost Virtual Instrument (VI) for monitoring the Power Quality (PQ) events. There are number of mathematical and machine intelligence techniques being used for analyzing the distorted, non-stationary current/voltage waveforms. Here in this paper a technique is used that visualizes the effect of various types of windows on non-stationary signals, and the primary focus is on finding the various harmonic components present. Fundamental frequency is estimated using Buneman Frequency Estimator and harmonic spectrogram is plotted using Short time Fourier Transform (STFT). The Dolph-Chebyshev window’s performance is found good and comparison is made. The zero padding technique is also implemented for the better detection of interharmonics. The system is developed on LabVIEW platform and the testing is done through simulation and live current/voltage input through data acquisition board.
Fabrication and Characterization of a Silicon Carbide Based Schottky Barrier Diode
(Springer, 2023-08) Singh, Dheerendra
In this work, we report the fabrication and characterization of a Schottky diode containing a metal–semiconductor Schottky junction. The metal–semiconductor Schottky contact was formed using nickel (Ni) as the metal and silicon carbide (4H-SiC) as the semiconducting material. The metal–semiconductor Schottky diode array was fabricated on 350-μm-thick 4H-SiC (0001) substrates. The Schottky contact was formed using Ni, and a triple layer of Ti/Pt/Au was used for the ohmic contact. Deposition of Ni-Cr alloy on 4H-SiC was carried out to improve the adhesion at the metal–semiconductor interface. Based on the current–voltage (I–V) characteristics, the device output parameter values for turn-on voltage, forward current at 5 V, reverse saturation current, barrier height (φB) and ideality factor (η) were 1 V, 2.57 mA, 652 nA, 0.935 eV and 1.296, respectively. A band diagram is proposed to explain the charge transport phenomena.
Feed forward modelling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series-parallel hybrid electric vehicle to improve fuel economy
(Springer, 2020-01) Singh, Dheerendra; Bansal, Hari Om
A hybrid electric vehicle is powered by: the internal combustion engine and the battery-powered electric motor. These sources have specific operational characteristics, and it is necessary to match these characteristics for the efficient and smooth functioning of the vehicle. The nonlinearity and uncertainties in hybrid electric vehicle model require an intelligent controller to control the energy sharing between battery and engine. In this work, a fuzzy logic-enabled energy management strategy for the hybrid electric vehicle based on torque demand, battery state of charge and regenerative braking is designed and implemented. The proposed energy management strategy allows engine and motor to maneuver in their efficient operating regions. The designed hybrid electric vehicle and its control strategy follow the driver commands and regulations on vehicle performance and liquid fuel consumption. MATLAB/Simulink is used to carry out simulations, and then, the whole system is validated in real time on hardware-in-the-loop testing platform. This work employs an FPGA-based MicroLabBox hardware controller to validate real-time behavior. The proposed scheme results in better fuel economy, faster response and almost nil mismatch between desired and achieved vehicle speeds.
Feed-forward modeling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series–parallel hybrid electric vehicle to improve fuel economy
(Springer, 2020-01) Bansal, Hari Om; Singh, Dheerendra
A hybrid electric vehicle is powered by: the internal combustion engine and the battery-powered electric motor. These sources have specific operational characteristics, and it is necessary to match these characteristics for the efficient and smooth functioning of the vehicle. The nonlinearity and uncertainties in hybrid electric vehicle model require an intelligent controller to control the energy sharing between battery and engine. In this work, a fuzzy logic-enabled energy management strategy for the hybrid electric vehicle based on torque demand, battery state of charge and regenerative braking is designed and implemented. The proposed energy management strategy allows engine and motor to maneuver in their efficient operating regions. The designed hybrid electric vehicle and its control strategy follow the driver commands and regulations on vehicle performance and liquid fuel consumption. MATLAB/Simulink is used to carry out simulations, and then, the whole system is validated in real time on hardware-in-the-loop testing platform. This work employs an FPGA-based MicroLabBox hardware controller to validate real-time behavior. The proposed scheme results in better fuel economy, faster response and almost nil mismatch between desired and achieved vehicle speeds.
Fuzzy logic and Elman neural network tuned energy management strategies for a power-split HEVs
(Elsevier, 2021-06) Bansal, Hari Om; Singh, Dheerendra
This paper focuses on optimal energy sharing between the two sources i.e., the internal combustion engine and the battery-powered electric motor in a hybrid electric vehicle (HEV). It is necessary that these sources operate in their efficient operating region while fulfilling the energy demanded by the vehicle to obtain the maximum fuel economy. As both of these sources have different operating characteristic and vehicle running conditions, the situation requires a smart controller to address this problem appropriately. In this work, fuzzy logic and Elman neural network-based adaptive energy management strategies (EMS) in an HEV are designed and implemented. The input parameters to these EMS are torque demand, battery state of charge, and regenerative braking. The proposed strategy aims to maximise the fuel economy while maintaining the battery health. A power-split HEV along with EMS is designed, modelled and simulated in MATLAB/Simulink first and then the whole system is validated in real-time using controller hardware in the loop testing platform (CHIL). The FPGA based MicroLabBox CHIL has been employed to test the system behaviour in real-time. The proposed EMS have been compared with conventional strategies and the comparison reveals that the Elman neural network-based method results in higher fuel economy, faster response, and minimal mismatch between desired and attained vehicle speeds.
Hardware Realization of a Single-Phase-Modified P-Q Theory-Based Shunt Active Power Filter for Harmonic Compensation
(Springer, 2019-08) Bansal, Hari Om; Singh, Dheerendra
This paper aims the harmonic compensation of inductive load using a single-phase Shunt Active Power Filter (SAPF). The instantaneous reactive power (p-q) theory is used in the controller to control the SAPF. This theory applies effectively for both, single- and three-phase systems. This theory is modified to achieve effective performance in single-phase systems. The system proposed has been simulated and analyzed in MATLAB, and then a lab prototype is developed and controlled using Arduino-based microcontroller. The response of the proposed system to variation in load is fast and takes care of sudden switching on/off.
Hardware-in-the-loop Implementation of ANFIS based Adaptive SoC Estimation of Lithium-ion Battery for Hybrid Vehicle Applications
(Elsevier, 2020-02) Bansal, Hari Om; Singh, Dheerendra
This paper presents an effective method to estimate the state of charge (SoC) of a Lithium-ion battery. This parameter is very crucial as it indicates the performance and health of the battery. The battery SoC estimation equivalent circuit provided in MATLAB has been modified by adding the 3- RC pairs in series with its internal resistance. The values of the RC pairs have been calculated mathematically by solving the circuit model, based on charging and discharging dynamics of the battery. The values of these parameters have also been optimized using a “lsqnonlin” function. The SoC of the battery is estimated using the combination of coulomb counting and open-circuit voltage methods to minimize the error in estimation. The obtained SoC is further corrected for errors using ANFIS based algorithms. The effect of temperature has also been accounted for modelling the battery and in SoC estimation. These obtained SoCs for 3 cases, i.e. without RC/with RC pairs and then tuned with ANFIS based optimization are compared for the same load. The parameter calculation method adopted here results in an efficient and accurate model that keeps track of correct battery SoC. The complete system is validated in real-time using hardware-in-the-loop laboratory setup.
High voltage gain reduced current ripple switched coupled inductor quasi-Z-source inverter
(Wiley, 2019-12) Bansal, Hari Om; Singh, Dheerendra
This article proposes an extended boost switched coupled inductor quasi-Z-source inverter (ESCL-q-ZSI) topology. The key features of ESCL-q-ZSI topology are high voltage gain, ripple-free continuous source current, and common ground between dc source and inverter circuit, and this makes it propitious for PV applications. Due to the presence of two different switched inductor (SL) structures, ESCL-q-ZSI topology offers high voltage gain at low shoot through duty ratio ( Dsh) as compared to reported switched inductor q-ZSI topologies. Low Dsh ensures high modulation index; hence, better output power quality is achieved. Moreover, both the SL structures used in ESCL-q-ZSI topology possess coupled inductors that aid in eliminating ripples in the source current and inductor currents. Thus, the average inductor current, in turn, inductor size required to obtain the same voltage gain gets reduced. This article is initiated with a brief literature review. It summarizes salutary factors in each chronologically developed switched inductor q-ZSI topology and remarks over limitations of each topology. Magnetic and mathematical considerations to design coupled inductor for SL structures are derived. The superiority of ESCL-q-ZSI over conventional topologies is projected through thorough comparative analysis. Effectiveness of the proposed topology is validated through a MATLAB/Simulink platform and a laboratory prototype.