World Electr. Veh. J., Volume 12, Issue 1 (March 2021) – 51 articles

This work develops scenario-based analyses for predicting in-vehicle performance degradation of automotive traction batteries. It combines recent capacity performance-based models of NCM-LMO Li-ion (Nickel Cobalt Manganese Oxide—Lithium Manganese Oxide) variant batteries with real-world vehicle driving data from different geographical areas of Europe. The analysis addresses different battery and vehicle architectures (PHEVs (Plug-in Hybrid Electric Vehicles) and BEVs (Battery Electric Vehicles)) combined with different recharging strategies and mobility patterns and environmental temperatures. The mobility pattern datasets used in this analysis refer to six European cities and include up to 508,609 private vehicles, corresponding to 1.78 billion GPS records, 9.1 million trips and parking events and a total driven distance of 106.1 million kilometers. The results show the effect that the environmental temperature, the recharging power, and the driven kilometers have on the calendar and cycling aging. The majority of the combinations of the considered vehicle architectures and recharge strategies do not lead to battery capacity drop below 80% of its nominal value in less than five calendar years for a usage profile of up to 1000 km/month. Full article

According to the complex fault mechanism of direct current (DC) charging points for electric vehicles (EVs) and the poor application effect of traditional fault diagnosis methods, a new kind of fault diagnosis method for DC charging points for EVs based on deep belief network (DBN) is proposed, which combines the advantages of DBN in feature extraction and processing nonlinear data. This method utilizes the actual measurement data of the charging points to realize the unsupervised feature extraction and parameter fine-tuning of the network, and builds the deep network model to complete the accurate fault diagnosis of the charging points. The effectiveness of this method is examined by comparing with the backpropagation neural network, radial basis function neural network, support vector machine, and convolutional neural network in terms of accuracy and model convergence time. The experimental results prove that the proposed method has a higher fault diagnosis accuracy than the above fault diagnosis methods. Full article

Electrification of public utility vehicles plays a vital role in the transition towards a more sustainable transport system. However, the adoption of electric vehicles (EVs) encounters varying challenges ranging from financing issues, government policies, and public acceptance. Using the Philippines as a case, this research applies political, economic, social, technological, legal, and environmental (PESTLE) analysis to determine how different drivers affect the adoption of EVs in the public transport system from various transport stakeholders’ vantage points. Survey results identified economic and technological factors as the main barriers to the adoption of electric public transport. This includes high investment and operational costs, lack of charging infrastructure, issues in driving range and use in different terrains, and the availability of EV parts and repair stations. On the other hand, the main enabler is the significant public support for the modernization of the public transport system through EVs, backed up by policy and legal drivers. For a zero-emission public transport system, this study recommends that the government should invest in sustainable sources of energy, develop more public infrastructure, diversify the transport sector, fund the development of locally made EVs, and initiate a massive information campaign in educating the public of its advantages. Full article

In this paper, the major factors that affect the performance of wireless power transfer systems, such as coil inner radius and coil number of turns, are discussed. A comparison of three coil shapes covering the coreless case, the case with ferrite, and the case with ferrite and aluminum is also carried out. Another comparison is proposed by addressing the combination of different coil shapes in the wireless power transfer (WPT)system. The analysis covers the coupling coefficient, the mutual inductance, and the self-inductance. Due to the complexity of calculating these parameters, the finite element analysis (FEA) method is adopted by using the Ansys Maxwell software. An introduction to the typical WPT system for electric vehicle charging is also presented. Full article

This article deals with an intelligent adaptive neural network (ANN) controller for a direct torque controlled (DTC) electric vehicle (EV) propulsion system. With the realization of artificial intelligence (AI) conferred adaptive controllers, the torque control of an electric car (eCAR) propulsion motor can be achieved by estimating the stator reference flux voltage used to synthesize the space vector pulse width modulation (SVPWM) for a DTC scheme. The proposed ANN tool optimizes the parameters of a proportional integral (PI) controller with real-time data and offers splendid dynamic stability. The response of an ANN controller is examined over standard drive cycles to validate the performance of an eCAR in terms of drive range and energy efficiency using MATLAB simulation software. Full article

Cycling is an increasingly popular mode of transport as part of the response to air pollution, urban congestion, and public health issues. The emergence of bike sharing programs and electric bicycles have also brought about notable changes in cycling characteristics, especially cycling speed. In order to provide a better basis for bicycle-related traffic simulations and theoretical derivations, the study aimed to seek the best distribution for bicycle riding speed considering cyclist characteristics, vehicle type, and track attributes. K-means clustering was performed on speed subcategories while selecting the optimal number of clustering using L method. Then, 15 common models were fitted to the grouped speed data and Kolmogorov–Smirnov test, Akaike information criterion, and Bayesian information criterion were applied to determine the best-fit distribution. The following results were acquired: (1) bicycle speed sub-clusters generated by the combinations of bicycle type, bicycle lateral position, gender, age, and lane width were grouped into three clusters; (2) Among the common distribution, generalized extreme value, gamma and lognormal were the top three models to fit the three clusters of speed dataset; and (3) integrating stability and overall performance, the generalized extreme value was the best-fit distribution of bicycle speed. Full article

Tire longitudinal forces of electrics vehicle with four in-wheel-motors can be adjusted independently. This provides advantages for its stability control. In this paper, an electric vehicle with four in-wheel-motors is taken as the research object. Considering key factors such as vehicle velocity and road adhesion coefficient, the criterion of vehicle stability is studied, based on phase plane of sideslip angle and sideslip-angle rate. To solve the problem that the sideslip angle of vehicles is difficult to measure, an algorithm for estimating the sideslip angle based on extended Kalman filter is designed. The control method for vehicle yaw moment based on sliding-mode control and the distribution method for wheel driving/braking torque are proposed. The distribution method takes the minimum sum of the square for wheel load rate as the optimization objective. Based on Matlab/Simulink and Carsim, a cosimulation model for the stability control of electric vehicles with four in-wheel-motors is built. The accuracy of the proposed stability criterion, the algorithm for estimating the sideslip angle and the wheel torque control method are verified. The relevant research can provide some reference for the development of the stability control for electric vehicles with four in-wheel-motors. Full article

Electric vehicles (EVs) have the main advantage of using sustainable forms of energy to operate and can be integrated into electrical power grids for better energy management. An essential part of the EV propulsion system is the type of motor used to propel the EV. Permanent magnet synchronous motors (PMSMs) have found extensive use due to various advantages such as high power density, excellent torque-to-weight ratio and smooth speed profile over the entire torque range. The objective of this paper was to improve the dynamic response in the speed profile for different driving conditions essential in EVs. This was done by using the finite control set model predictive control (FCS-MPC) algorithm for PMSM and by comparing and evaluating the control strategies of a PMSM used in an EV by taking two case studies. The classical control, namely field-oriented control (FOC), of PMSMs is slow to adopt the dynamic changes in the system. The proposed FCS-MPC algorithm for PMSMs provides an improved dynamic response and a good steady-state response for the different driving conditions shown in both cases. In addition, the Worldwide Harmonized Light Vehicles Test Procedure (WLTP) is used to evaluate the FCS-MPC-controlled PMSM to depict its superior performance by matching its speed profile. The results are verified in the hardware in the loop strategy using OPAL-RT. Both the results confirm that the FCS-MPC algorithm, when compared with the conventional FOC, is superior in aspects of steady-state and dynamic responses for various torque and speed profiles. Full article

Plug-in vehicles (PEVs), which include battery-only electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), have steadily grown in sales amidst various incentive programs, but much speculation exists on when PEVs would become cost-competitive without incentives. This research adopts a bottom-up approach for estimation of purchase cost, and total cost of ownership (TCO). Baseline predictions, as well as sensitivity analysis (with more favorable conditions for PEVs) are generated for 2030. Results show that the five-year TCO of some PEVs could be less than an equivalent-sized conventional internal combustion-engine (CICE) vehicle, but only in the more optimistic scenarios where the cost of batteries and motors decrease more rapidly than the baseline prediction, and when combined with either higher gasoline prices or longer annual distance travelled. However, without subsidies or incentives, purchase cost parity between PEVs and CICEs was not realized in any of the considered 2030 scenarios. Full article

The durability and reliability of battery management systems in electric vehicles to forecast the state of charge (SoC) is a tedious task. As the process of battery degradation is usually non-linear, it is extremely cumbersome work to predict SoC estimation with substantially less degradation. This paper presents the SoC estimation of lithium-ion battery systems using six machine learning algorithms for electric vehicles application. The employed algorithms are artificial neural network (ANN), support vector machine (SVM), linear regression (LR), Gaussian process regression (GPR), ensemble bagging (EBa), and ensemble boosting (EBo). Error analysis of the model is carried out to optimize the battery’s performance parameter. Finally, all six algorithms are compared using performance indices. ANN and GPR are found to be the best methods based on MSE and RMSE of (0.0004, 0.00170) and (0.023, 0.04118), respectively. Full article

An induction motor is a key device for an industrial machine. The installation misalignment of the motor will result in derating problems and energy consumption that is generally used to analyze signal faults using the fast Fourier transform (FFT) method. Problems with the rotor affect the non-stationary signal and FFT can be utilized to analyze this problem inefficiently. This paper proposed the testing and analysis of faults in an eccentric rotor at different levels using the stator current detection technique and the calculation of the energy signal coefficient via the wavelet decomposition (WD) method. The experimental results showed that an increase in eccentricity had a linear relation with the energy signal, where R² was 80.81%. Moreover, the test results illustrated that the proposed method was more efficient than FFT and applicable to motor fault analysis and application in the industrial. Full article

An Electric propulsion (E-propulsion) system for ASEAN (Association of Southeast Asian Nations) long-tail boat is proposed in this article. It offers several advantages over a traditional internal combustion engine propulsion system. Besides low noise and zero-emission, characteristics of electric engine (E-engine) allow regenerative braking and starting the propeller in the water. A design of E-engine has been achieved through finite element analyses and lump-parameter thermal simulations. It shows better performances than Honda GX270 internal combustion engine in terms of volume, weight, torque, and power. A full scale prototype of E-engine was manufactured. Experiments have been conducted on an engine test bench. Torque, power, efficiency and temperatures were well aligned with the simulation results. Full article

Optimization of a two-wheeler hybrid electric vehicle (HEV) is a typical challenge compared to that for four-wheeler HEVs. Some of the challenges which are particular to two-wheeler HEVs are throttle integration, smooth switching between power sources, add-on weight compensation, efficiency improvisation in traffic, and energy optimization. Two power sources need to be synchronized skillfully for optimum energy utilization. A prominent variant of HEV is that it easily converts conventional scooters into parallel hybrids by “Through-the-Road (TTR)” architecture. This paper focuses on three switching control strategies of HEVs based on the state of charge, fuzzy logic, and neural network. Further, to optimize energy usage, all these control strategies are compared. Energy management control for the TTR model is developed with vehicle parameters in the Simulink environment and simulated using the “World Harmonized Motorcycle Test Cycle” (WMTC) drive cycle. The multivariable input model is presented with a fuzzy rule-based hybrid switching control. A similar system is also modeled with a neural network-based decision control and the observations are tabulated for the fuel economy and energy management. Simulation results show that the neural network-based optimization results in minimal energy consumption among all three hybrid operations. Full article

Electric vehicle technologies have seen rapid development in recent years. However, Reliability, Availability, and Maintainability (RAM) related concerns still have restricted large-scale commercial utilization of these vehicles. This paper presents an approach to carry out a quantitative RAM analysis of a plug-in electric vehicle. A mathematical model is developed in the Markov Framework incorporating the reliability characteristics of all significant electrical components of the vehicle system, namely battery, motor, drive, controllers, charging unit, and energy management unit. The study shows that the vehicle’s survivability can be increased by improving its components’ restoration rates. The paper also investigates the role of a charging station on the availability of the vehicle. It illustrates how the grid power supply’s reliability influences the operational effectiveness of a plug-in electric vehicle. The concepts that are presented in the article can support further study on the reliability design and maintenance of a plug-in electric vehicle. Full article

Stator-slot circumferentially magnetized PM machines (SSCMPMMs) have high fault-tolerant capability. In this paper, the SSCMPMMs with full-pitched windings and different stator slot/rotor pole numbers are investigated, together with the influence of key geometric parameters. It shows that the 12 stator-slots 7 rotor-poles (12S7R) machine delivers the highest torque. It is then compared with the SSCMPMM with tooth-coil windings. The results show that when they have the same active length, the 12S7R machine delivers significantly higher torque and higher efficiency. Furthermore, when the machine length is over around 140 mm, the 12S7R machine is more advantageous in producing high torque and high efficiency. A prototype is manufactured and tested to validate the theoretical analyses. Full article

This paper deals with the winding arrangement of multi-phase fractional-slot permanent magnet (PM) synchronous machines (FSPMSMs), with emphasis on the enhancement of their open-circuit fault-tolerance capability. FSPMSMs are reputed by their attractive intrinsic fault-tolerance capability, which increases with the number of phases. Of particular interest is the open-circuit fault-tolerance capability, which could be significantly enhanced through the parallel connection of the coils or suitable combinations of the coils of each phase. Nevertheless, such an arrangement of the armature winding is applicable to a limited set of slot-pole combinations. The present work proposes a design approach that extends the slot-pole combinations to candidates that are characterized by a star of slots including three phasors per phase and per winding period. It has the merit of improving the tolerance against open-circuit faults along with an increase in the winding factor of multi-phase machines. Special attention is paid to characterization of the coil asymmetry required for the phase parallel arrangement. A case study, aimed at a finite element analysis (FEA)-based investigation of the open-circuit fault-tolerance of a five-phase FSPMSM, is treated in order to validate the analytical prediction. Full article

Electric vehicles are a leading candidate in the clean energy market. This paper aims to analyse the feasibility of the deployment of electric buses (EB) based on the existing bus routes in Brunei, by the use of life cycle cost analysis and the analysis of the parameters that influence the overall life cycle cost. The findings from the study revealed that EB are significantly more expensive than diesel buses (DB), with their acquisition and maintenance costs contributing substantially to their overall life cycle cost. In order to promote EB deployment, the government needs to look simultaneously into providing subsidies for EB and imposing taxes on DB, the provision of charging infrastructure, and ensuring maintenance capability, as well as increasing the current subsidised diesel price. It was also shown that increasing the cost of diesel to the average US diesel price of USD$3.101/L, an initial subsidy of USD$67,586 towards the purchase of EB, and a tax of USD$67,586 for the purchase of DB would allow EB to compete in the market, with the amount of tax and subsidy being gradually reducible over time, as EB and battery technology becomes more mature. From an environmental perspective, the emissions from EB come out higher than the emissions from DB. The efficiency of electric power generation needs to be enhanced, and renewable energy sources and the adoption of carbon capture technology need to be explored in order to exploit the full benefit of EB and ensure more environmentally sustainable bus operation. Full article

Autonomous electric buses (AEB) have widely been envisioned in future public transportation systems due to their large potential to improve service quality while reducing operational costs. The requirements and specifications for AEBs, however, remain uncertain and strongly depend on the use case. To enable the identification of the optimal vehicle specifications, this paper presents a holistic design optimization framework that explores the impacts of implementing different AEB concepts in a given set of routes/network. To develop the design optimization framework, first, a multi-objective, multi-criteria objective function is formulated by identifying the attributes of bus journeys that represent overall value to the stakeholders. Simulation models are then developed and implemented to evaluate the overall performance of the vehicle concepts. A genetic algorithm is used to find the concepts with the optimal trade-off between the overall value to the stakeholders and the total cost of ownership. A case study is presented of a single bus line in Singapore. The results show an improvement in the waiting time with the use of a smaller sized AEB with a capacity of 20 passengers. However, the costs and emissions increase due to the requirement of a larger fleet and the increase in daily distance traveled compared to a 94-passenger capacity AEB. Full article

Public Transport (PT) planning requires a detailed evaluation of the fleet energy consumption, usually depending on the specific characteristics of the bus service network. These include topography, climate and operational features. In this work, we focus on the additional air conditioning (AC) energy consumption, proposing a method to evaluate the extra energy consumption based not only on climate variables, but also on the PT planned service. Results are presented for a large part of the provincial capitals and regions of Italy, and clearly show that overconsumption for air conditioning are significantly affected by the daily mileage distribution, with large variance even when climatic conditions are similar. The mileage data are extracted from GTFS databases, widely available for PT applications. The developed tool allows us to apply this methodology to any urban and extra-urban area. Reference AC consumption related to climate conditions are derived from a measurement campaign hold in Cagliari (Sardinia, Italy) during September 2018, within the National Research Program on the Electric System. A discussion on how to optimize the use of climatic data is also presented, resulting in the choice to use Heat Index as unique independent variable for air conditioning energy consumption calculation. A methodology to compute the Heat Index from climatic variables for large domains as, for instance, the Italian regions, was also developed. Full article

This paper deals with the complete design procedure, implementation and control software realization for a multi-converter charging station with reduced grid impact due to local electromechanical energy storage. In particular, energy storage is accomplished by a dedicated flywheel designed and built for this purpose. The proposed charging station was designed for ultra-fast charging procedures presenting a strongly reduced impact on the electrical grid. Modes of operations are described with reference to pure electric buses in public transportation applications. Full article

The prediction of lane change intention of vehicles is an important part of the decision planning and control systems of intelligent vehicles. In the dynamic and complex traffic environment, the behaviors of traffic participants interact and influence each other. In lane change prediction, it is necessary to study the predicted vehicle and surrounding vehicles as an interactive correlation system. Otherwise, great errors are made in the motion prediction. Based on this, the motion state of the predicted vehicle, the position relationship between the predicted vehicle and lane, as well as the motion state of vehicles around the predicted vehicle are considered systematically in this paper, and the prediction of lane change intention of vehicles is studied. The influence of the three above-mentioned factors on the prediction of lane change intention is analyzed in this paper. On the basis of screening the prediction features of lane change intention, the lane change intention of vehicles is predicted by a feed-forward neural network. The data collected by the virtual driving experiment platform are divided into a training set, a verification set, and a test set. The neural network parameters of vehicles’ lane change intentions are identified by a training set, and the effect of prediction is tested by a verification set and a test set. The results show that the accuracy of the prediction model is high. The model is compared with the model of common features at the present stage and the model based on a Support Vector Machine, and the results show that the accuracy of the prediction model proposed in this paper was improved by 6.4% and 2.8%, respectively, compared with the two models. Finally, the virtual driving experiment platform was used to predict the lane change intention of the front vehicle and the vehicle in the left adjacent lane. The results show that, based on the same model and input features, the lane change intention of the front vehicle and the vehicle in the left adjacent lane can be predicted by the model at 2.8 s and 3.4 s before the lane change, and the model is a certain generality for the prediction of lane change intention of adjacent vehicles. Full article

A surface-mounted permanent magnet (SPM) machine is widely used in many auxiliary parts of an electric vehicle, so its design level directly influences the performance of the electric vehicle. In the design process of the SPM machine, selecting the appropriate stator slot and rotor pole combination and pole arc coefficient is a necessary and important step. Therefore, in this paper, a 750 W machine is set as an example to research stator slot and rotor pole combinations and pole arc coefficients for the SPM machine. First, the design schemes of machines adopting different stator slot and rotor pole combinations are determined according to the winding coefficient, stator size, and electromagnetic performance requirements. Further, finite element models of SPM machines with different stator slot and rotor pole combinations are established by Ansys Maxwell. On this basis, the back electromotive force (back EMF), cogging torque, electromagnetic torque, and loss and efficiency of SPM machines are calculated and compared to select the better stator slot and rotor pole combinations. Further, effects of pole arc coefficient on cogging torque and electromagnetic torque are also researched to guide the selection of the pole arc coefficient in the design process of the SPM machine. Conclusions achieved in this paper will provide guidance for design of the SPM machine. Full article

A variety of measures are currently being taken on both the national and international levels in order to mitigate the negative effects of climate change. The promotion of electric mobility is one such measure for the transport sector. As a key component in a more environmentally-friendly, resource-saving, and efficient transport sector, electric mobility promises to create better sustainability. Several challenges still need to be met to exploit its full potential. This requires adapting the car technology, the value chain of vehicles, loads on the electricity network, the power generation for the drive, traffic, and charging infrastructure. The challenges to this endeavor are not only technical in nature, but they also include social acceptance, concerns, and economic, as well as ecological, aspects. This paper seeks to discuss and elucidate these problems, giving special focus to the issues of driving range, phenomenon of range anxiety, charging time, and complexity of the charging infrastructure in Germany. Finally, the development of social acceptance in Germany from 2011 to 2020 is investigated. Full article

This article proposes a mathematical model of an axial flux induction motor (AFIM) with one stator and one rotor. The model is based on the expression for the electromagnetic torque, which presents a function of two independent variables: the axial length of the stator core and the flux density in the air gap. This allows calculating the main dimensions of the motor with the highest possible torque density. Thus, developed model is suitable for designing the motor of specified volume with maximum torque, and solving the inverse problem of minimizing the machine volume with the specified torque. The detailed output of the model and the results of the calculations for the low-power engine powered by voltage of 7.35 V (RMS) are given. The results are validated using FEM in ANSYS software: with the outer motor diameter of 0.11 m, the flux density in it reaches 1.2 T. Full article

Striving to achieve sustainable development goals and taking care of the environment into the policies of car manufacturers forced the search for alternative sources of vehicle propulsion. One way to implement a sustainable policy is to use electric motors in cars. The observable development of the electric car market provides consumers with a wide spectrum of choices for a specific model that would meet their expectations. Currently, there are 53 different electric car models on the primary market in Poland. The aim of the article was to present the performed market segmentation, focused on identifying the similarities in the characteristics of electric car models on the Polish market and proposing their groupings. Based on the classification by the hierarchical cluster analysis algorithm (Ward’s method, squared Euclidean distance), the market division into 2, 3, and 4 groups was proposed. The Polish EV market segmentation took place not only in terms of the size and class of the car but primarily in terms of performance and overall quality of the vehicle. The performed classification did not change when the price was additionally included as a variable. It was also proposed to divide the market into 4 segments named: Premium, City, Small, and Sport. The segmentation carried out in this way helps to better understand the structure of the electric car market. Full article

This paper presents a comparative study of two consequent-pole switched-flux permanent magnet (CP-SFPM) machines with different U-shaped PM arrangements. In order to address the flux barrier effect in a sandwiched SFPM machine, two different alternate U-shaped PM designs are introduced to improve the torque capability, forming two CP-SFPM machine topologies. In order to reveal the influence of different magnet designs on the torque production, a simplified PM magneto-motive force (MMF)-permeance model is employed to identify the effective working harmonics in the two CP-SFPM machines. The torque contributions of the main working harmonics are subsequently quantified by a hybrid finite-element (FE)/analytical method. Multi-objective genetic algorithm (GA) optimization is then employed to optimize the design parameters of the proposed CP-SFPM machines. In addition, the electromagnetic characteristics of the CP-SFPM machines with two U-shaped PM arrangements are investigated and compared by the FE method. Finally, a 6/13-pole CP-SFPM machine with an optimally selected U-shaped PM structure is manufactured and tested to validate the FE analyses. Full article