Electric Vehicle Simulation Research Articles

GPS data integration to reduce driving emissions of MHEVs in real operating conditions

Increasingly emission reduction requests and environmental pollution cut require improved optimization of current transportations. Control strategies and latest vehicles technologies developed in the automotive industry must be optimized, taking into account more information is possible from cars sensors to save energy and reduce emissions. The paper presents a possible strategy for reducing emissions with integration of GPS data in a Mild Hybrid Electric Vehicle simulator. In this study, real GPS data are evaluated to improve the system and introduce real environmental conditions in the system. The data obtained are analysed selectively in the paper. This paper is aimed to investigate the impact of real conditions on fuel consumption. Through theoretical analysis, the conclusion will be drawn that GPS technology is attractive to reduction of emissions.

Dynamic modeling and Simulation of Electric Vehicles

This paper presents the benefits of EV’s with conventional IC vehicles. Along with that we discuss about various Motor drive technologies (MDT),Battery charging technologies (BCT),Energy source technologies, configurations of EV’s and HEV’s. Based on the dynamic modeling of EV’s we reduce the tractive effort on the Electric vehicles.

EleMA: A reference simulation model architecture and interface standard for modeling and testing of electric vehicles

Abstract In automotive development, simulation models are gaining significance, in particular in the early phases of verification and validation. According to the current state-of-the-art, there is no standardized simulation framework to achieve a seamless transition in the conception, implementation and integration of complex system simulations. In this paper, a reference simulation model architecture for electric vehicles is presented, which is proposed as a standard for real-time and non-real-time closed-loop simulations. The proposed Electric Modeling Architecture (EleMA) is intended as an extension of standardized model exchange formats by defining standardized, functional and signal-based interfaces of electric vehicle simulation models. It is designed independently of the utilized tool chain or exchange format of the simulation model components and enables their functional compatibility and exchangeability. Initially, an overview of standardized model exchange formats as well as the main design ideas of the proposed reference architecture are presented, followed by a short description of the applied specification methodology. EleMA provides all users a reference model including the contained components, a formalized description in the form of use case diagrams and a definition of the variant-independent component interfaces for each individual component. The implementation of simulation model components according to EleMA guarantees from an architectural point of view a functional compatibility of the elements on system level and thus improves reusability and exchangeability of simulation components. The last section demonstrates use cases to highlight the advantages of the reference architecture and quantifies the average effort reduction exemplary for one use case.

Modeling and Simulation of PEM Fuel Cell Electric Vehicle with Multiple Power Sources

This paper provides detailed modeling and simulation of a proton exchange membrane (PEM) fuel cell electric vehicle. The power supply system consists of a PEM fuel cell and a battery bank. The power management system effectively manages the supply flow from the dual power supply system without compromising the efficient working condition of both power supply systems. The mathematical modeling of each subsystem of the hybrid electric vehicle is presented. All the subsystems are then combined and simulated and the results are presented and discussed.

Future electricity demand and flexibility potential of private households

In the upcoming years, a disruptive revolution of the electricity demand in terms of load patterns and annual consumption is expected. Electricity from renewable energy sources can be used to decarbonise further sectors like the mobility sector. These new appliances, like electric vehicles, significantly increase and reshape the electricity demand of private households while efficiency gains slightly reduce the electricity consumption. Furthermore, the ongoing digitalisation allows an efficient controlling of the flexibility of these appliances. These developments make detailed investigations of the future electricity demand and flexibility potentials of private households inevitable. For this purpose, a Bottom-Up simulation method has been developed and is presented in this study. Using time use data of household members, activity profiles are derived based on a time-dependent Markov-chain model. Based on these activity profiles, different submodels for the simulation of electric appliances, lighting, heating and electric vehicles are used. The investigations in this contribution show the influence of new appliances like electric vehicles on the electricity demand of private households in terms of peak load and energy demand. Furthermore, the results allow a better estimation of the flexibility potential of appliances like washing machines based on the simultaneity of their usage.

Electric Vehicles Inductive Power Transfer System Modeling, Simulation and Control

Till the moment, electric vehicles charging statically using stationary stations, microgrids or other known conventional methods still represents a big problem for this industry, and a worrying snag to users. Due to different problems of electric vehicles charging using static methods, most of recent electric vehicles' researches are interested in the subject of charging these vehicles using inductive power transfer (IPT) or the so-called dynamic charging. This method depends mainly on transformer theory. In this paper, an IPT system is proposed, modeled in state-space form, simulated using MATLAB package and analyzed. The IPT system analysis focused on calculating one of the main system parameters - magnetic coupling coefficient and finding its optimal value. At this value, the transient dynamic voltage and current response of the circuit is found. Also, a fractional order proportional-integral-derivative (FO-PID) controller is proposed to enhance and smoothen the power signals (Voltage and current).

Empirical Study on the Efficiency of an LPG-Supplied Range Extender for Electric Vehicles

A range extender is an auxiliary power unit, usually consisting of an internal combustion engine and an electric generator, which is used to charge a battery of an electric vehicle in order to increase its range. This paper considers a range extender supplied with liquefied petroleum gas (LPG). The aim is to provide detailed data on thermal efficiency, brake specific fuel consumption (BSFC), and unit emission of carbon dioxide (CO2) in a broad spectrum of range extender operating conditions defined by rotational speed and torque. The experimental investigation has been conducted using a laboratory test stand equipped with an energy dissipation system of adjustable resistance. Measurement results, including fuel flow rate, were processed using custom algorithm for generating maps, i.e., two-dimensional dependencies of the considered parameters on the rotational speed and torque. The maps obtained for LPG supply were compared with those for gasoline supply. The results demonstrated feasibility of LPG-supplied range extender. Its BSFC and thermal efficiency were at a comparable level to those obtained for gasoline supply, but with less CO2 emission. The empirical data collected has been adopted in the simulation of extended-range electric vehicle in a driving cycle, showing the potential of utilizing the results of this study.

Speed Control of IDDB and SVPWM Controlled PMSM Motor in Fuel Cell Based Electrical Vehicle

The prominence of Fuel Cell Electric Vehicles (FCEV) has been soaring in technologies being implemented in electric automobiles due to their main advantages of eco-friendly nature, bountiful efficiency and extreme reliability .In this paper we deal with the simulation of electric vehicles that are fuel cell based. The voltage at the output stack of fuel cell is considerably low, hence it is increased by rendering IDDB converter with closed loop control. This type of boost converter with closed loop control is also utilized to priorate the converter output voltage consistent regardless of the pressure levels in the fuel cell. The output of the boost converter is coupled to the inverter for developing AC to run PMSM. Gating signals are produced to the inverter by the use of Space Vector PWM technique and the inverter output is supplied to the PMSM drive by means of an LC filter in order to diminish the ripples in the inverter output . In this work, in order to achieve better performance above induction motors such as higher speed, torque efficiency PMSM drive has been proposed . The results are verified by simulation techniques using MATLAB/Simulink.

Modeling and Simulation of Electric Vehicle to Optimize Its Cost and Range

In the present days, the vehicles are primarily operated for transportation applications. The conventional energy sources like oil and gas are used as fuel sources of various vehicles. Since the year 2000, electric vehicles are commonly used in various countries. Within the previous few years, the electric vehicle remains a constant topic for the research community. The drive train can be the main challenge for the researchers. In this paper, we developed an EV drive train configuration with the help of AC motors. The developed model contains a battery source, AC motors (Induction (squirrel cage) and Synchronous (PMSM), motor controller (DTC (Direct torque control) and FOC (field Oriented control), PI control, wheels configuration (Front and Rear) and vehicle body. The model developed on the Simulink tool of Matlab. A Metaheuristic optimization algorithm WOA (Whale Optimization Algorithm) used to optimize the gain parameters of PI control. WOA based optimized PI controllers can adjust their gains values (Kp and Ki) in correspondence to deviations of EV speed and torque and results in stable speed and torque conditions. The proposed optimization controllers possess advantages over conventional controllers in terms of its robustness, to achieve better EV stability, no speed overshoot and accurate speeds.

Modeling and Simulating a Battery for an Electric Vehicle Based on Modelica

Battery is the key technology to the development of electric vehicles, and most battery models are based on the electric vehicle simulation. In order to accurately study the performance of LiFePO4 batteries, an improved equivalent circuit model was established by analyzing the dynamic characteristics and contrasting different-order models of the battery. Compared to the traditional model, the impact of hysteresis voltage was considered, and the third-order resistance–capacitance (RC) network was introduced to better simulate internal battery polarization. The electromotive force, resistance, capacitance and other parameters were calibrated through battery charge and discharge experiments. This model was built by using Modelica, a modeling language for object-oriented multi-domain physical systems. MWorks was used to implement the cycle conditions and vehicle simulation. The results show that the third-order RC battery model with hysteretic voltage well reflects the dynamics of a LiFePO4 battery. The difference between the simulated and measured voltages is small, with a maximum error of 1.78%, average error of 0.23%. The validity and feasibility of the model are verified. It can be used in unified modeling and simulation of subsequent multi-domain systems of electric vehicles.

Optimal Scheduling Strategy of Distribution Network Based on Electric Vehicle Forecasting

Based on the Monte Carlo method, this paper simulates, predicts the load, and considers the travel chain of electric vehicles and different charging methods to establish a predictive model. Based on the results of electric vehicle simulation prediction, an optimal scheduling model of the distribution network considering the demand response side load is established. The firefly optimization algorithm is used to solve the optimal scheduling problem. The results show that the prediction model proposed in this paper has a certain reference value for the prediction of an electric vehicle load. The electric vehicle is placed in the optimal scheduling resource of the distribution network, which increases the dimension of the scheduling resources of the network and improves the economics of the distribution network operation.

Analysis of the Current Electric Battery Models for Electric Vehicle Simulation

Electric vehicles (EVs) are a promising technology to reduce emissions, but its development enormously depends on the technology used in batteries. Nowadays, batteries based on lithium-ion (Li-Ion) seems to be the most suitable for traction, especially nickel-manganese-cobalt (NMC) and nickel-cobalt-aluminum (NCA). An appropriate model of these batteries is fundamental for the simulation of several processes inside an EV, such as the state of charge (SoC) estimation, capacity and power fade analysis, lifetime calculus, or for developing control and optimization strategies. There are different models in the current literature, among which the electric equivalent circuits stand out, being the most appropriate model when performing real-time simulations. However, impedance models for battery diagnosis are considered very attractive. In this context, this paper compares and contrasts the different electrical equivalent circuit models, impedance models, and runtime models for battery-based EV applications, addressing their characteristics, advantages, disadvantages, and usual applications in the field of electromobility. In this sense, this paper serves as a reference for the scientific community focused on the development of control and optimization strategies in the field of electric vehicles, since it facilitates the choice of the model that best suits the needs required.

Simulation of Future Electric Vehicle Charging Behavior—Effects of Transition from PHEV to FEV

The Netherlands is a frontrunner in the field of public charging infrastructure, having one of the highest number of public charging stations per electric vehicle (EV) in the world. During the early years of adoption (2012–2015), a large percentage of the EV fleet were plugin hybrid electric vehicles (PHEV) due to the subsidy scheme at that time. With an increasing number of full electric vehicles (FEVs) on the market and a current subsidy scheme for FEVs only, a transition of the EV fleet from PHEV to FEV is expected. This is hypothesized to have an effect on the charging behavior of the complete fleet, and is reason to understand better how PHEVs and FEVs differ in charging behavior and how this impacts charging infrastructure usage. In this paper, the effects of the transition of PHEV to FEV is simulated by extending an existing agent-based model. Results show important effects of this transition on charging infrastructure performance.

Subsidy and Pricing Model of Electric Vehicle Sharing Based on Two-Stage Stackelberg Game – A Case Study in China

Electric vehicle sharing provides an effective way to improve the traffic situation and relieve environmental pressure. The government subsidy policy and the car-sharing operator’s pricing strategy are the key factors that affect the large-scale application of electric vehicle sharing. To address this issue, a subsidy and pricing model for electric vehicle sharing based on the two-stage Stackelberg game is proposed in this paper according to the current situation in China. First, an electric vehicle sharing operation mode under government participation is constructed. Then, a two-stage Stackelberg game model involving the government, the car-sharing operator and the consumers is proposed to determine the subsidy rates and pricing strategies. The improved particle swarm optimization algorithm is used to obtain the Nash equilibrium of the model. Also, the influence of private car cost and shared travel comfort on subsidy rates and pricing strategies is analyzed. Finally, the simulation of electric vehicle sharing in a town of China is carried out to investigate the performance of the proposed subsidy and price model. The simulation results show that the model rationally formulates subsidy policies and pricing strategies of the electric vehicle sharing to balance the interests of the three participants, mobilizing users’ enthusiasm while guaranteeing the benefits of the government and operator, making the overall benefit optimal.

A Multi-Agent System for Smart Energy Management Devoted to Vehicle Applications: Realistic Dynamic Hybrid Electric System Using Hydrogen as a Fuel

Real-time simulation test beds for new zero-emission hybrid electric vehicles are considered as an attractive challenge for future transport applications that are fully recommended in the laboratory environment. In contrast, new zero-emission hybrid electric vehicles have a more complicated charging procedure. For this reason, an efficient simulation tools development for hydrogen consumption control becomes critical. In this vein, a New Zero Emission Hybrid Electric Vehicle Simulation (NZE-HEVSim) tool for the dynamic Fuel Cell Hybrid-Electric System is proposed to smartly control multisource activities. The designed system consists of a proton-exchange membrane fuel cell used to provide the required energy demand and a Supercapacitor system for energy recovery assistance in load peak or in fast transient. To regulate the supplied power, an efficient Real-Time Embedded Intelligent Energy Management (RT-EM-IEM) is implemented and tested through various constraints. The proposed intelligent energy management system aims to act quickly against sudden circumstances related to hydrogen depletion in the basis required fuel consumption prediction using multi-agent system (MAS). The proposed MAS strategy aims to define the proper operating agent according to energy demand and supply. The obtained results prove that the designed system meets the objectives set for RT-EM-IEM by referring to an experimental velocity database.

A Series Hybrid Electric Vehicle Simulation and Analysis of Fuel Consumption Alteration in Different Driving Cycles

With decrease in amount of carbon fuels and aims of creating a cleaner environment, researches on hybrid electric vehicle technology have increased in years. The purpose of this study is to observe the change in fuel consumption of a simulated hybrid electric vehicle in different driving cycles. For this research, a series hybrid electric vehicle is modelled on MATLAB/Simulink. Subsequently, for simulating the tour of the vehicle, multiple driving cycles are modelled on the software and fed to vehicle model. For instance FTP-75, NEDC and UDDS are benefited and also a route from Turkey, the road from Istanbul to Ankara is modelled and simulated. Behavior of the vehicle on this route is also observed. After analyzing vehicle behavior in all these cycles, fuel consumption in each case is calculated and compared. As the result of this research, the most affordable cycle for this vehicle model is selected and possible ways of decreasing fuel consumption in other driving cycles is discussed.

Simulation of diesel hybrid electric vehicle containing hydrogen enriched CI engine

Hydrogen enrichment on diesel engines is a proven solution for both minimizing the undesirable emissions and fuel consumptions. Also, hybrid electric vehicles which manufactured for the same goal too, are playing an important movement during three decades in transportation sector. The combination of these two common-purpose technologies will give possibility to production of hybrid electric vehicles which have hydrogen-enriched internal combustion engine, in the near future.At this study, four type modelled vehicle; stock diesel vehicle (V1), hydrogen enrichment diesel vehicle (V2), hybrid electric vehicle which contains same diesel engine (V3) and hybrid electric vehicle that powered by hydrogen enrichment diesel engine (V4); simulated with AVL simulation tools for compared the performance and emission values, for the first time. V1 is outfitted by 3.0 L diesel engine. V2 is the hydrogen enriched version of V1 which hydrogen addition is conducted via intake manifold with 8% (vol/vol) enrichment. V1 and V2 were simulated under AVL Boost tool for analyzing the effects of hydrogen addition clearly. After that, V3 and V4 were modelled with AVL Cruise. V3 and V4 were coupled an electric motor (30 kW) with appropriate battery. In terms of performance and emissions results, vehicle types with hydrogen enriched diesel engines were given promising outputs when compared with without ones. In particular, V4 has revealing excellent performance. Under this study's circumstances, when compared V4 between stock one, 4.26% improvement was achieving on vehicle performance parameters. Additionally, the combined fuel consumption, NOx emission and CO2 emission decreases with 14.32%, 15% and 33% respectively, for comparison between V4 and V1.

Strategies for Implementing Public Service Electric Bus Lines by Charging Type in Daegu Metropolitan City, South Korea

The large-scale adoption of electric vehicles in the public sector is essential for achieving emission reduction targets for transportation. In particular, the replacement of buses with internal combustion engines, which travel long distances and produce massive greenhouse gas emissions, by their electric counterparts can drastically reduce emissions. A variety of electric buses with different power supply systems are currently available, and their performance, charging type, battery capacity, and operating environment are related parameters that must be addressed for their successful and massive adoption. For instance, the appropriate charging type of electric buses depends on conditions, such as the operating environment. In this study, we determined the optimum capacity of electric bus batteries by considering the electric bus range, battery depth of discharge, and deterioration cost while using ADVISOR, which is a MATLAB-based electric vehicle simulator. In addition, we assessed the energy consumed and charging time according to the operating environments of electric buses. Finally, an economic efficiency analysis allowed for determining the appropriated charging type for electric buses. By integrating these data and analyses, we propose a comprehensive plan for selecting the most appropriate charging type according to the operating environment of these electric vehicles. We expect that the proposed plan will contribute to the adoption of electric buses and achieve the greenhouse gas reduction targets set by South Korea.

Development of XBW in-wheel-motor-drive electric vehicle simulation platform

The unique distributed drive mode of the in-wheel-motor-drive electric vehicle (IWMDEV) is known as the ultimate form of automobile chassis technology. In order to meet the verification requirements of the SBW (steer-by-wire)/DBW (drive-by-wire)/BBW (break-by-wire) IWMDEV control algorithm, a 19 degrees of freedom (DOFs) dynamic model of the 4WID/4WIS/4WIB vehicle, including the vertical vibration, is established. According to the characteristics of XBW (x-by-wire) electric vehicle, modular design is used to design the structure and signal flow of the simulation platform. And the modeling methods and dynamic equations of each actuator are given. In addition, under different working conditions, the dynamic response quality of the simulation platform is compared and verified by CarSim. These experiments show that the simulation platform has high precision and can be used to analyze the transient and steady state response characteristics of the XBW IWMDEV under various working conditions.

EVLibSim: A tool for the simulation of electric vehicles’ charging stations using the EVLib library

Electric Vehicles (EVs) are considered an efficient alternative to internal combustion engined ones, aiming to reduce global CO2 emissions. In the last years, EVs are entering the market in an increasing pace. In contrast to conventional cars, EVs have a more complicated recharging procedure. Thus, the development of tools for the efficient simulation of the charging of large numbers of EVs is critical. In this vein, EVLibSim is a tool for the simulation of EV activities at a charging station level. EVLibSim unifies EVLib’s primary functions such as the charging and dis-charging of batteries, battery swapping, as well as parking/inductive charging. EVLib is a Java library that provides a simple, yet efficient framework for the management of a number of Electric Vehicle (EV) activities, at a charging station level, within a Smart Grid. EVLibSim provides a great variety of configuration options such as the types and number of chargers, the available energy, the waiting queues, etc. Furthermore, through plots and overview dashboards each user can supervise the operation of the tool in real time. Both EVLib’s and EVLibSim’s efficiency and scalability have been tested in realistic scenarios, while the correctness and safety of the code have been verified using state of the art tools. Finally, the user experience of the EVLibSim has been evaluated and improved through a detailed user evaluation.