Energy Efficiency Of Electric Vehicles Research Articles

Comprehensive Comparison between Hybrid and Electric Vehicles Using a Multi-Dimensional Techno-Economic Assessment Diagram: Concept and Application

This paper presents a visualization methodology, in the form of a multi-dimensional techno-economic assessment diagram, to comprehensively illustrate the relationship between assumptions (sets of input parameters) and results (corresponding output variables). This methodology is applied to analyze the lifecycle costs and CO2 emissions of hybrid vehicles (HVs) and electric vehicles (EVs). This paper then develops an eight-dimensional interactive diagram showing the relative advantages of HVs or EVs in the input space consisting of the following parameters: HV fuel efficiency; EV energy efficiency, total mileage travelled gasoline price, electricity price, battery price, gasoline CO2 intensity, and electricity CO2 intensity. This methodology provides a map illustrating the comprehensive relationship between the inputs and outputs in the model used, where specific scenarios (specific sets of inputs and their outputs) are represented by points plotted on the map. This methodology can be used in systematic comparisons of electric vehicles and related uncertainty analyses.

A comprehensive approach for optimal design of magnetorheological dampers

Magnetorheological dampers have been used in automotive industry and civil engineering applications for shock and vibration control for some time. While such devices are known to provide reliable shock and vibration suppression, there exist emerging applications in which the magnetorheological dampers have to be optimized in terms of power consumption and overall weight (e.g. energy-efficient electric vehicles). Utilizing traditional optimal design approaches to tackle those issues can sometimes lead to convergence problems such as getting trapped in a local extremum and failing to converge to the global optimum. Furthermore, manufacturing limitations are usually not taken into account in the optimization process which may hamper achieving an optimal design. In this article, we present a method for optimal design of magnetorheological dampers by utilizing mathematical optimization and finite element analysis. The proposed method avoids infeasible solutions by considering physical constraints such as fabrication limitations and tolerances. This approach takes every single feasible solution into account so that the final solution would be the global extremum of the optimization cost function. The proposed approach is applied to optimize a complex magnetorheological damper structure with different types of materials such as steel and AlNiCo. In particular, we present the design of a valve-mode magnetorheological damper with AlNiCo integrated as its core. A magnetorheological damper prototype is manufactured based on the proposed optimization method and tested experimentally.

Stochastic Model Predictive Control of Air Conditioning System for Electric Vehicles: Sensitivity Study, Comparison, and Improvement

A stochastic model predictive controller (SMPC) of air conditioning (AC) system is proposed to improve the energy efficiency of electric vehicles (EVs). A Markov-chain based velocity predictor is adopted to provide a sense of the future disturbances over the SMPC control horizon. The sensitivity of electrified AC plant to solar radiation, ambient temperature, and relative air flow speed is quantificationally analyzed from an energy efficiency perspective. Three control approaches are compared in terms of the electricity consumption, cabin temperature, and comfort fluctuation, which include the proposed SMPC method, a generally used bang-bang controller, and dynamic programming as the benchmark. Real solar radiation and ambient temperature data are measured to validate the effectiveness of the SMPC. Comparison results illustrate that SMPC is able to improve the AC energy economy by 12% compared to the rule-based controller. The cabin temperature variation is reduced by more than 50.4%, resulting with a much better cabin comfort.

Efficiency comparison of electric vehicles powertrains with dual motor and single motor input

Two novel dual motor input powertrains are proposed to improve the energy efficiency of electric vehicles (EVs). The first powertrain is based on a dual motor with planetary gear transmission (DMPGT), which connects two motors to the sun gear and ring gear respectively, and the carrier is engaged with output shaft. Two band brakes equipped on the sun gear and ring gear can realize three driving modes. The second powertrain is based on a dual motor with parallel axle transmission (DMPAT). It also provides three driving modes through switching on and off the two motors. To evaluate the two proposed powertrains, they will be compared with the widely adopted single motor with 1-speed and with 2-speed powertrains. The gear ratios of the powertrains are selected aiming at the vehicle dynamic performance, while the gear or mode shifting is designed to maximize the efficiency of EVs through an instantaneous optimization algorithm. The simulation results of the two proposed powertrains in three typical driving cycles demonstrate that the EVs equipped with both DMPGT and DMPAT have a higher overall efficiency than the EVs equipped with single motor input powertrain.

Electronic–magnetic gearing motor analyses and simulations for electric vehicles

This study presents an innovative electronic-magnetic geared motor technology for electric vehicles (EVs). The motor has been designed and simulated. The electronic-magnetic gearing (EMG) connects parallel, series or hybrid connections of stator windings into gears to accommodate the different speed and torque demands in the drive cycle. The objective of the EMG is to increase the speed and torque range of the motor and reduce current draw from the batteries. A 1.5 kW prototype EMG motor was built and tested on a test rig at Electronica Products Ltd. A comparison simulation of an EMG motor compared with a traditional permanent magnet synchronous motor was also carried out. The result proves that the theory of EMG is sound and it has great potential for energy efficiency in EVs, especially for the powertrain units.

A four-step control algorithm and downshift schedule of a seamless shift transmission equipped on electric vehicles during the regenerative braking process

To improve dynamic performance and energy efficiency of electric vehicles, various methods are adopted, one of which is to equip each electric vehicle with a seamless shift transmission that can ma...

Effect of road gradient on regenerative braking energy in a pure electric vehicle

A regenerative brake system significantly improves the energy efficiency of electric vehicles, but road gradient can adversely affect fuel economy and vehicle control. This study seeks to explore the effects of road gradient on the regenerative brake system on the basis of driving information collected by global positioning systems (GPS) and inertial sensors, including road gradient and vehicle speed. Then optimization is made of conventional parallel control strategy, serial control strategy with fixed front–rear brake force allocation, and serial control strategy with optimal energy recovery. By calculating the contribution ratio to energy consumption reduction in each of the three strategies based on a model of pure electric vehicle’s energy flow, the roles that road gradient plays are carefully investigated. Simulation results show that our proposal for taking road gradient into account helps to design more efficient strategies of regenerative braking systems.

Energy Efficiency Improvement via Bus Voltage Control of Inverter for Electric Vehicles

Although great effort has been devoted with various approaches on the improvement in energy efficiency of electric vehicles, much of the focus has been on the design of electric devices and power electronic systems and of energy storage systems with energy management strategies. This paper proposes a bus voltage control method that actively and dynamically controls the bus voltage applied to the inverter through a dc/dc converter, such that it tracks the rotational speed of the motor, that aimed to improve the energy efficiency of the inverter, or the overall energy efficiency of power electronic systems. A detailed energy efficiency model is first developed that takes into account the inverter loss and motor iron loss. Some detailed and in-depth analyses on energy efficiency have been conducted that conclude that the inverter's energy efficiency is largely related to the voltage applied, and the voltage is further closely related to the rotational speed of the motor. Simulations and in-vehicle experiments under a New European Driving Cycle (NEDC) have been conducted that demonstrate the effectiveness of the proposed method on the improvement in energy efficiency of the inverter, as well as the system as a whole.

Differences in Energy Consumption in Electric Vehicles: An Exploratory Real-World Study in Beijing

Electric vehicles (EVs) are widely regarded as a promising solution to reduce air pollution in cities and key to a low carbon mobility future. However, their environmental benefits depend on the temporal and spatial context of actual usage (journey energy efficiency) and the rolling out of EVs is complicated by issues such as limited range. This paper explores how the energy efficiency of EVs is affected and shaped by driving behavior, personal driving styles, traffic conditions, and infrastructure design in the real world. Tests have been conducted with a Nissan LEAF under a typical driving cycle on the Beijing road network in order to improve understanding of variations in energy efficiency among drivers under different urban traffic conditions. Energy consumption and operation parameters were recorded in both peak and off-peak hours for a total of 13 drivers. The analysis reported in this paper shows that there are clear patterns in energy consumption along a route that are in part related to differences in infrastructure design, traffic conditions, and personal driving styles. The proposed method for analyzing time series data about energy consumption along routes can be used for research with larger fleets of EVs in the future.

Design and implementation of an innovative electronic magnetic gearing motor

ABSTRACTThis paper presents an innovative electronic magnetic geared (EMG) motor. The motor is designed and tested. This electronic EMG motor assembles parallel, serial or hybrid connections of stator windings into gears to accommodate the different speed and torque demands in the drive cycle. The objective of EMG is to increase the maximum speed and maximum torque range of the motor. A 1.5 kW prototype EMG motor was built up and tested on a test rig. The test results prove that the theory of EMG is correct. It will have a large positive impact on the energy efficiency of electric vehicles.

Wireless Power Transfer and In-Vehicle Networking Integration for Energy-Efficient Electric Vehicles

This paper presents the wireless power transfer (WPT) technology based on inductive coupling and the design challenges of a hybrid energy harvester (EH) circuit as a promising solution to promote the energy efficiency of the electric vehicles (EVs). The design methodologies of ultra-low power (ULP) electronic module based on low leakage conditioning and processing device are detailed based on nanoscale transistor technology so that the WPT and hybrid EH can be implemented for self-powered devices in EVs. Moreover, in-vehicle network design verification based on a new power-aware behavioral model formulation and extraction for high-speed and ULP transceivers that enables the transient prediction of power and ground currents and voltages when multiple drivers are simultaneously switching for signal-power integrity evaluation. The derivation of the proposed model is based on the analysis and extension of the input/output buffer information specification (IBIS). The analysis of the previous IBIS and Mpilog modeling approaches is followed by a new model formulation along with a well-designed characterization and parametric extraction procedure.

Modelling the multilevel structure and mixed effects of the factors influencing the energy consumption of electric vehicles

To improve the accuracy of estimation of the energy consumption of electric vehicles (EVs) and to enable the alleviation of range anxiety through the introduction of EV charging stations at suitable locations for the near future, multilevel mixed-effects linear regression models were used in this study to estimate the actual energy efficiency of EVs. The impacts of the heterogeneity in driving behaviour among various road environments and traffic conditions on EV energy efficiency were extracted from long-term daily trip-based energy consumption data, which were collected over 12months from 68 in-use EVs in Aichi Prefecture in Japan. Considering the variations in energy efficiency associated with different types of EV ownership, different external environments, and different driving habits, a two-level random intercept model, three two-level mixed-effects models, and two three-level mixed-effects models were developed and compared. The most reasonable nesting structure was determined by comparing the models, which were designed with different nesting structures and different random variance component specifications, thereby revealing the potential correlations and non-constant variability of the energy consumption per kilometre (ECPK) and improving the estimation accuracy by 7.5%.

Cooperative control of regenerative braking and friction braking in the transient process of anti-lock braking activation in electric vehicles

Regenerative braking significantly improves the energy efficiency in electric vehicles. Cooperative control between regenerative braking and friction braking during anti-lock braking control is a critical issue in brake system coupling. For safety concerns, regenerative braking is often terminated at the beginning of anti-lock braking control. Oscillations between activation of an anti-lock braking system and exit from anti-lock braking system control may occur under poorly matched control parameters. To solve these problems, we propose an index that indicates the possibility of activation of an anti-lock braking system. It is derived by a fuzzy logic algorithm which is based on the estimated regenerative braking torque, the estimated friction braking torque and other vehicle state variables. Regenerative braking can be adjusted on the basis of the index to ensure that such braking is of a low level when an anti-lock braking system is activated. Simulations and experiments are carried out to evaluate the effectiveness of the index. The results show that regenerative braking decreases as the index increases, thereby improving the braking safety and the driving comfort during the transient process of activation of an anti-lock braking system.

Development and Analysis of Switched Capacitor Four Quadrant DC-DC Converter for Hybrid Electric Vehicle

Background/Objectives: The main objective of this research is to develop a bi-directional four quadrant DC-DC converter for an energy efficient electric vehicle. Methods/Analysis: The model of electric vehicle is designed using MATLAB software. The results confirm that the proposed DC-DC converter structure is highly reliable, lighter in weight, smaller in volume, with good efficiency, less electromagnetic interference and lower current or voltage ripple. Findings: The issues on global warming and fossil fuels depletion have created opportunities to Electric Vehicle (EV). The main characteristics of Energy storage system in vehicles include energy density, power density, lifetime, cost and maintenance. Most of the electric and hybrid electric configurations use two energy storage devices, one with high energy storage capacity, called the Main Energy System (MES) and the other with high power capacity called the Auxiliary Energy Storage System (AESS). Other challenge in electric vehicle is to maintain the state of charge within the allowable limits and sharing of energy between the storage devices. For proper sharing of energy between the storage devices, DC-DC converter plays a crucial role. Novelty/Improvement: A novel Switched Capacitor DC-DC power converter and their controllers are investigated.

Analysis of downshift’s improvement to energy efficiency of an electric vehicle during regenerative braking

Downshift during regenerative braking helps to improve the energy efficiency of electric vehicles. Two main problems are involved in the downshift process. One is the determination of optimal downshift point, and the other is the cooperative control of regenerative braking and hydraulic braking. In order to achieve a systemic solution to these problems, a hierarchical control strategy is brought forward for an electric vehicle with a two-speed automated mechanical transmission. For the upper controller, an off-line calculation and on-line look-up table method is adopted to obtain the optimal downshift point, and a series regenerative braking distribution strategy is designed. For the medium controller, a nonlinear sliding mode observer is designed to obtain the actual hydraulic brake torque. For the lower controller, cooperative control of regenerative braking and hydraulic braking is given to ensure brake safety during downshift process, and a resembling pulse width modulation method is proposed to regulated the hydraulic brake torque. Simulation results and hardware-in-loop test show that the proposed algorithm is effective in improving the energy efficiency of electric vehicles.

Fully Electrified Regenerative Braking Control for Deep Energy Recovery and Maintaining Safety of Electric Vehicles

Recycling braking energy is significant to improve the total energy efficiency of electric vehicles (EVs). Moreover, braking safety must be maintained under complex conditions. As the actuator, the electric traction motor has much better features than the internal combustion engine, e.g., faster torque response and capability for energy feedback. From the perspective of energy efficiency and safety, highlighting regenerative braking is a meaningful but challenging problem. In this paper, a braking system using only electric motors/generators as the actuators is investigated, in which the energy may be potentially fed back to the onboard energy storage system (ESS) as much as possible. The energy that may be recovered to the ESS is analyzed. To maintain the stability and to improve the performance of the regenerative braking in unknown tire–road conditions, a knowledge-based methodology in a hierarchical control structure is proposed, where the maximum adhesion force and the motor reference torque (MRT) are determined online. The proposed methodology avoids the complex determination of the optimum slip ratio, while acquiring nearly the optimum antiskid braking performance. Simulation and experiment were carried out to validate the effectiveness.

An Analysis of Regenerative Braking and Energy Saving for Electric Vehicle with In-Wheel Motors

Based on the structural features of electric vehicle (EV) driven by in-wheel motors and the characteristics of low speed as well as high torque for in-wheel motors, regenerative braking method for in-wheel motors has been presented. All braking torque for vehicle deceleration is output by in-wheel motors under Medium-intensity braking condition for the sake of recovering the maximum braking energy. The vehicle dynamics model that includes the hydraulic braking system and in-wheel motors driving system has been built by AMESim software. Simulation has been carried out for vehicle driving conditions by NEDC cycle and FTP75 cycle. The result shows that the recovery rate of braking energy is increased dramatically by in-wheel motor braking method. The energy efficiency of electric vehicle has been improved more than 30%. It is significant for electric vehicles to increase driving range and reduce costs.

Optimal energy management strategy for battery powered electric vehicles

Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios.

THE PERFORMANCE OF CONDENSER UNDER DIFFERENT VEHICLE SPEEDS

Due to the concern in energy shortage and environmental protection, electric vehicle is considered to be a substitute for the conventional gasoline-powered vehicles due to its characteristics of high efficiency and no emission. However, the load of air conditioning causes a serious problem for electric vehicles, especially in tropical and subtropical areas. The compressor of conventional air conditioning system is driven by engine and its speed is thus coupled to vehicle speed. In electric vehicles, the compressor is driven by electric motors and compressor speed could be decoupled to vehicle speed. This mechanism provides an opportunity to improve the energy efficiency of electric vehicle since the operation of air conditioning system may be independent of vehicle speed. The purpose of this paper is to find out the electric fan operation model as vehicle speed is varied. This paper was to establish a theoretical model for the condenser of automotive air conditioner and to conduct simulation to evaluate the effect of vehicle speed on the cooling capacity and sub-cooling of condenser. Results of simulation demonstrated that vehicle with 6 km h-1 speed has the 5°C of sub-cooling at 0.0266 kg s-1 of refrigerant flow rate and the cooling capacity was 4.93 kW. In this study, an increase of 16.6% in cooling capacity can be reached as the speed of vehicle was raised from 6 to 110 km h-1 and can promote the sub-cooling to 19.5°C. It was also found that the cooling capacity of air conditioner is extremely sensitive to vehicle speed while the vehicle is running at low speed. Furthermore, increases in the vehicle speed resulted in reduction of the length of superheat region from 17.5 to 8.5 cm. Finally, a correlation among these variables and the simulated cooling capacity was obtained in this study, enabling the relevant researchers to evaluate automotive air conditioner performance under different vehicle speeds more easily.

Research on Maglev Flywheel Energy Storage System for Electric Vehicle

In order to improve the energy efficiency of electric vehicle (EV) power battery, and increase the start-up power of EV, a kind of maglev flywheel battery storage energy system is designed on EV, it is active suspension controlled at five degrees of freedom. The system suspension control principle is expounded, and the radial single freedom transfer function of the maglev flywheel is established combining with a digital PID control algorithm. The frequency spectrum characteristic of the transfer function and the flywheel rotor trajectory curve are simulated, and the 30000 r/min rotation experiment of the maglev flywheel battery prototype is realized. The experiment result shows that the maglev flywheel rotor may high speed and steadily spin, and has good energy storage ability. The maglev flywheel battery storage energy system can assist the EV power battery work, improves the battery charge and discharge properties and prolongs the service life of the motive power battery.