Electric Vehicle Powertrain Research Articles

Experimental platform for studying energy regeneration in electric vehicle powertrains

Investigation into the energy consumption in electric vehicles (EVs) plays a pivotal role in determining their autonomy and assessing the electric system performance across diverse operational scenarios. This study focuses on the concept of energy regeneration, encompassing the recovery and storage of kinetic mechanical energy during braking or descent in EVs. Employing control systems in power electronics becomes necessary to establish a seamless workflow across operational quadrants to ensure efficient energy regeneration in an electric machine functioning as both a motor and a generator. To seamlessly integrate new technologies into practical applications, it is essential to conduct thorough evaluations in laboratories prior to deployment. This paper introduces an experimental platform specifically designed to analyze energy consumption and storage in EVs by emulating their powertrains in a controlled laboratory environment. The platform comprises key components for emulating the powertrain of a single-motor electric vehicle with single-axle traction, including a power converter configured in two quadrants, an energy storage system, a primary rotating electric machine, and a mechanically coupled point load torque (another motor). This paper provides a detailed guide on implementing such a laboratory and for facilitating the testing of diverse motor technologies and controllers under varied operational conditions. This comprehensive approach allows for the assessment of electromechanical system efficiency, focusing on both energy recovery and comprehensive control of electric power converters. Validation tests conducted under urban conditions and on steep terrains demonstrate the effectiveness of the platform in analyzing the energy efficiency of both the induction machine and the power controller.

Finite Element Analysis and Optimization of High Speed E-mobility Seal

Background: The use of electric vehicles is expected to increase day by day. The operating conditions of the rotary shaft seals used in the powertrain of electric vehicles are more challenging than those of internal combustion engines. The maximum operating temperature of seal used in electric vehicles is 150℃ and the maximum operating speed is 16,000RPM. It is impossible for a standard seal with a garter spring not to leak under these operating conditions, which has led us to turn to alternative designs. Objective: The objective of starting this study is to develop a new generation rotary shaft seal to be used in electric vehicles with finite element analysis (FEA) and optimization. Methods: During this study, finite elements, optimization and geometry development methods were used. First of all, alternative spiral knurled seal that can operate at high speeds was designed in this study. Secondly, our alternatively designed seal was tested to determine lifetime. Results: When we checked the results coming from test machines, the first design seal had approximately 5g of leakage at the end of 7 days. In the examinations made after the experiment, it was observed that the spirals were deleted at the end of 7 days. A finite element model of the first designed seal was created and radial load control was performed. When the radial load value obtained from the finite element model and the experimental radial load value are compared, it is seen that there is a deviation of around 4.3%. In the light of these data, the accuracy of the FEA model created in the Abaqus has been proven. The created finite element model was optimized within the boundary conditions with the help of Isight. A prototype of the optimized design seal was produced and a life-time test was carried out. The prototype seal of the optimized design had approximately 4g of leakage after 13 days under the same test conditions. Since the lifetime requested by the customer is 10 days, the optimization made on the seal is considered appropriate. The lifetime of the seal was approximately 95% improved. Conclusion: As a result, a new generation rotary shaft seal that can be used in electric vehicles, which is the aim of our study, has been developed. The prototype rotary shaft seal has been validated according to DIN 3761 specification.

An Assessment of Accurate Range Estimator for Electric Vehicle Applications

Abstract: The world’s primary modes of transportation are facing two major problems: rising oil costs and increasing carbon emissions. As a result, electric vehicles (EVs) are gaining popularity as they are independent of oil and do not produce greenhouse gases. However, despite their benefits, several operational issues still need to be addressed for EV adoption to become widespread. One of the main obstacles for the acceptance of EV’s is the driver’s fear of being stranded by a depleted battery. In other words, accurate estimation of the remaining SOC is required to provide positive edge towards adoption of EV. In this work, an EV is tested for a drive line cycle of 10 Km for a trip, and key parameters such as elevation, speed, body dynamics, vehicle dimensions, on track speed have been collected. A model of EV power train is developed in MATLAB Simulink from the data logged and a static app is being developed which estimates the vehicle dynamic forces, power consumption, energy utilized for the trip, State of Charge (SOC) and remaining mileage of the vehicle.

Efficiency Analysis of Ipoh Driving Cycle Using Fuel Powered and Electric Vehicle Powertrain Model in Simulink

Efficiency Analysis of Ipoh Driving Cycle Using Fuel Powered and Electric Vehicle Powertrain Model in Simulink

A Critical Analysis of Quadratic Boost Based High-Gain Converters for Electric Vehicle Applications: A Review.

Conventional DC-DC boost converters have played a vital role in electric vehicle (EVs) powertrains by enabling the necessary voltage to increase to meet the needs of electric motors. However, recent developments in high-gain converters have introduced new possibilities with enhanced voltage amplification capabilities and efficiency. This study discusses and evaluates the state-of-the-art high-gain DC-DC converters for EV applications based on the Quadratic Boost Converter (QBC). Research into innovative topologies has increased in response to the increasing demand for efficient and high-performance power electronic converters in the rapidly expanding EV industry. Due to its ability to provide more significant voltage gains than conventional boost converters, the QBC has become a viable option for meeting the unique requirements of EV power systems. This survey focuses on the efficiency, power density, and overall performance parameters of QBC-based high-gain converters. The literature review provides a foundation for comprehending power electronics converters' trends, challenges, and opportunities. The acquired knowledge can enhance the design and optimization of high-gain converters based on the QBC, thereby fostering more sustainable and efficient power systems for the expanding electric mobility industry. In the future, the report suggests that investigating new high-gain converter design methodologies will reduce component stress and enhance the intact system efficiency.

Numerical and experimental investigations on the vibration behavior of a high-speed planetary gearbox

Increasing the speed of the electric motor can significantly improve the power density of the powertrain of EVs (Electric Vehicles), resulting in a smaller size and thus weight and cost advantages. Achieving acceptable NVH behavior becomes more difficult at higher speeds, partly because the excitation frequencies of the gears cover a wider frequency range and therefore higher natural frequencies can also be directly excited. In the Speed4E joint research project, a high-speed electromechanical powertrain was developed, manufactured, and tested to investigate the main challenges on the NVH- and efficiency-behavior of high-speed powertrains. The high-speed design of the Speed4E drivetrain results in maximum electric motor speeds of up to 50,000 rpm, combined with a torque of up to 45 Nm at the transmission input shafts. This study presents the experimental results on the vibration behavior of the high-speed planetary gearbox, a comparison with the corresponding results of a highly efficient calculation method of the gearbox vibration excitation, and the theoretical background of the calculation method is presented. The results indicate the potential to improve the vibration behavior of high-speed drives in EVs and provide a deep understanding of the challenges associated with high speeds.

Hybrid Electric Vehicle Powertrain Mounting System Optimization Based on Cross-Industry Standard Process for Data Mining

The meticulously engineered powertrain mounting system of hybrid electric vehicles plays a critical role in minimizing vehicle vibrations and noise, thereby enhancing the longevity of vital powertrain components. However, developing and designing such a system demands substantial time and financial investments due to intricate analysis and modeling requirements. To tackle this challenge, this study integrates data mining technology into the design and optimization processes of the powertrain mount system. The research focuses on the powertrain mounting system of a transverse four-cylinder hybrid electric vehicle, employing the CRISP-DM (Cross-Industry Standard Process for Data Mining) methodology to establish a data-mining prediction model for mounting stiffness. This model utilizes three data mining algorithms—Multi-SVR, MRTs, and MLPR—to assess their predictive accuracy concerning mounting system stiffness estimation. A comparative analysis reveals that the MRTs algorithm outperforms others as the most effective prediction model. The proposed predictive model elucidates the quantifiable correlation between vibration isolation performance and installation stiffness, overcoming complexities associated with traditional modeling approaches. Applying this model in powertrain mounting system design showcases the efficacy of the CRISP-DM-based approach, significantly enhancing design efficiency without compromising prediction accuracy.

The transition to electrified vehicles: Evaluating the labor demand of manufacturing conventional versus battery electric vehicle powertrains

The shift from traditional internal combustion engine vehicles (ICEVs) to electric vehicles (EVs) has raised concerns about displacement of automotive manufacturing labor. Prior studies have mixed findings, and have been hindered by a lack of shop floor-level data on the labor hours required for ICEV and EV manufacturing. We collect detailed data from leading automotive manufacturers on the production process steps and labor inputs required to build key ICEV and battery electric vehicle (BEV) powertrain components. Our novel data set covers 252 process steps, with data on a further 78 process steps from the existing literature. We build a production process model that estimates the labor hours required to produce ICEV and BEV powertrain components at different production volumes and labor efficiency levels. We find that, accounting for production and assembly of battery packs, the labor intensity required for the manufacturing of BEV powertrain components is larger than for ICEV powertrain components. This difference in labor intensity holds even when comparing the highest-efficiency estimates for BEV production with the lowest efficiency-estimates for ICEVs. This finding depends on our shop-floor operations modeling approach and could not be derived from recent approaches focusing on part counts. Our results imply that vehicle electrification could lead to more automotive manufacturing jobs, at least in the short- to medium-term. While there are potential jobs to support transitions for incumbent automotive workers, the feasibility of these transitions will depend on geographic co-location of new battery production capacity with current ICEV production sites, and on matching between the skills of the automotive workforce and the demands of new EV jobs.

KPI-related monitoring approach for powertrain system in hybrid electric vehicles

This paper introduces a novel monitoring method related to key-performance-indicators (KPIs), specifically tailored for the hybrid electric vehicle (HEV) powertrain system. The proposed method establishes a new KPI that better reflects the performance of the HEV powertrain system. Through the application of partial least squares and contribution plot method, it excels in minimizing data scale and precisely monitoring HEV powertrain faults. Diverging from current methodologies, this method demands minimal prior knowledge and solely relies on previously observed HEV data. The simulation results demonstrate the method's capability to detect engine and motor overheating faults while accurately diagnosing their root causes. In summary, this innovative method marks a significant departure from existing approaches, providing a robust and powerful tool for state monitoring in the HEV powertrain system.

Autonomous Gate Drivers Tailored for Triangular Current Mode-Based Zero-Voltage Switching Two-Level Three-Phase Inverters for Electric Vehicle Drive Systems

The demand for highly efficient and dynamic electric vehicles (EVs) has increased dramatically. The traction inverter, a pivotal component in an EV powertrain, plays a crucial role. This study is dedicated to designing a traction inverter with focus on achieving high efficiency and elevated power density and mitigating electromagnetic interference (EMI) issues. To realize these objectives, autonomous gate drivers (AGDs) are proposed and designed using LTspice simulation software. The aim is to achieve zero voltage switching (ZVS) at both turn-on and turn-off through the utilization of triangular current mode (TCM) control on the gate driver. The AGDs implement a current modulation scheme by sensing the current and voltage and generating gate-source voltage signals with minimal delays. The implemented current modulation scheme by the AGDs results in an efficiency exceeding 99% for a 10 kW power rating. The sinusoidal output waveforms not only contribute to extending the motor lifespan by mitigating sharp-edge voltages but also bring advantages such as reduced switch stress, decreased EMI, and simplified thermal management.

Modeling and simulation of photovoltaic powered battery-supercapacitor hybrid energy storage system for electric vehicles

Energy storage is crucial for the powertrain of electric vehicles (EVs). Battery is a key energy storage device for EVs. However, higher cost and limited lifespan of batteries are their significant drawbacks. Therefore, to overcome these drawbacks and to meet the energy demands effectively, batteries and supercapacitors (SCs) are simultaneously employed in EVs. A solar photovoltaic (PV) powered battery-supercapacitor (SC) hybrid energy storage system has been proposed for the electric vehicles and its modeling and numerical simulation has been carried out in MATLAB Simulink. The SC is used to supply the peak power demand and to withstand strong charging or discharging current peaks. It also improved the battery pack's durability and extended its life. Different topologies of battery and SC have been explored and their capacity to manage the battery stress is assessed. The passive topology is found to be the most suitable for the proposed model due to its ease of implementation and absence of control scheme. A hybrid topology is used to share the power across batteries, supercapacitors and the PV system. In the proposed hybrid energy storage system, a sudden load on the battery is shifted towards the capacitor and thus, the battery heating is reduced, that ultimately improved the vehicle performance and reduced the charging time. In addition, the supercapacitor stored a lot of energy in a short period of time and delivered more power to the load without experiencing any life-span deterioration. The results indicated that employing a passive DC-DC converter and hybrid energy storage system (HESS) reduced the battery power by 52 %, while the passive HESS system reduced the motor current by 94 %. The supercapacitor also recovered 51 % more energy while starting and can offer peak power more efficiently than a battery.

Study on methanol-hydrogen engine in extended-range electric vehicles

The demand for clean and efficient new vehicle models is steadily increasing. Methanol-hydrogen engines use methanol as the main fuel and can recover the heat from engine exhaust to dissociate part of methanol into hydrogen-rich syngas. The syngas is recirculated back into the engine cylinder to improve combustion. Therefore, methanol-hydrogen engines have a higher energy utilization efficiency. This paper designed a methanol-hydrogen engine system based on a Miller cycle methanol engine. Bench tests showed that combusting methanol and dissociated methanol gas together could accelerate the fuel burn rate and improve the engine’s fuel economy. At a fixed engine speed of 2500 r/min, the BSFC of the methanol-hydrogen engine was reduced up to 5.55% compared to the original methanol engine. Further, a methanol-hydrogen extended-range electric vehicle powertrain model was built in Simulink. Simulation results indicated that, under the WTLC cycle, the methanol-hydrogen engine achieved a 22.60% reduction in fuel consumption per 100 km and saved 58.89% in fuel costs compared to the conventional gasoline engine. The methanol-hydrogen engine presented potential application in the extended-range electric vehicle.

A systematic approach to design electric vehicle powertrains: model-based simulation and real-world application

A systematic approach to design electric vehicle powertrains: model-based simulation and real-world application

A systematic approach to design electric vehicle powertrains: model-based simulation and real-world application

A systematic approach to design electric vehicle powertrains: model-based simulation and real-world application

A High Efficiency Non-Isolated Three-Phase Unfolding Based Electric Vehicle Powertrain

A High Efficiency Non-Isolated Three-Phase Unfolding Based Electric Vehicle Powertrain

Comprehensive Analysis of DC/DC Converters for Electric Vehicles Applications: Topologies and Future Perspectives

In order to implement the global sustainable development strategy, reduce the burden of traditional fuel vehicles on the environment, and at the same time, due to the increasing oil prices, more and more people are reluctant to use fuel vehicles, the global automobile industry. The centre of gravity has gradually shifted from traditional industrial energy vehicles to electric vehicles. As an integral part of the electric vehicle powertrain, the DC/DC converter has the important function of supplying power to the power steering system, air conditioning and other auxiliary equipment.This paper describes in detail the DC/DC converters that provide power for electric vehicles, describes in detail the different types of DC/DC converters as well as the different topologies, and analyses the characteristics of each topology and the method of providing power to the circuit by drawing the circuit of the different topologies. Next, the advantages and disadvantages of various topologies are compared, and improvement methods and future prospects are proposed for the shortcomings of different topologies.

Hydrogen Fuel Cell Aiming at Vehicle Propulsion: Onboard or Off-Board Electricity Generation?

In response to the global energy crisis and climate change, hydrogen has been pointed out as promising fuel to be part of the green energy transition. Thus, countries worldwide have released policies to support and increase the hydrogen industry. Therefore, investigations regarding how hydrogen can be utilized best as a fuel should be addressed to evaluate its potential applications. Since transportation is responsible for 37% of the carbon emissions from the end-use sectors, it is of interest to consider hydrogen fuel for vehicle propulsion. There are two main alternatives that might be considered for the electricity generation from hydrogen: 1) a hydrogen fuel cell onboard the electric vehicle or 2) a hydrogen fuel cell off-board powering the electric vehicle.Therefore, in this work, we propose the modeling and simulation from hydrogen fuel to wheels of the two different systems using the WLTP as the driving cycle reference. For the onboard system, the following components were considered: the vehicle dynamics, the gear, the motor, the inverter, the battery, and the fuel cell system on board (fuel cell vehicle powertrain). For the off-board system, the following components were considered: the vehicle dynamics, the gear, the motor, and the inverter for the battery electric vehicle powertrain, followed by the charger, the grid, and the fuel cell system off-board. The components were modeled as further described.The vehicle dynamics were modeled mathematically and the weight difference between the vehicles was taken into account. The gear was a single-step gear. The motor was an eight-pole PMSM and the inverter three-phase IGBT. The battery for both was modeled as a lithium-ion battery with different sizes, with the battery for the fuel cell vehicle being much smaller. Capacity values similar to commercialized vehicles were used (4 and 300 Ah). The fuel cell was modeled as a commercialized fuel cell with 63% peak efficiency. For the fuel cell vehicle, a control strategy was implemented to split the power demand between the fuel cell and the battery. The control strategy was based on the state of charge of the battery and the power demand for each point of the cycle.The simulation results have shown a slightly higher efficiency and lower hydrogen consumption for the onboard system compared to the off-board system. Even though there were more losses associated with the battery and the fuel cell in the onboard system, the losses associated with vehicle weight and the off-board power electronics related to the off-board system were more significant to the overall energy consumption. Thus, the results suggest that if hydrogen is available as a fuel aimed at vehicle propulsion using it onboard is more efficient than using it off-board.

Electric vehicle energy consumption modelling and analysis: a Malaysia case study

Previously, the Electric vehicle (EV) range anxiety greatly hindered EV adoption. The fear of being stranded due to running out of battery becomes the main concern among EV drivers. This critical issue can be solved by deploying a bigger battery in EVs. However, deploying bigger size battery contributes to the higher price of the EV itself. Hence, the optimal design of the EV powertrain is a critical factor in ensuring EV meets the users’ needs and, simultaneously, can be owned by the potential owners at an affordable price. Accurate assessment of EV energy consumption is crucial in designing an optimal EV powertrain, particularly for developing energy-efficient driving techniques in both manual and autonomous driving. One method is to perform a real-life experiment to determine the EV energy consumption, which is expensive and time-consuming. An alternative to real-world testing is creating an EV energy consumption model with the existing driving cycles. This paper studies the parameters contributing to EV energy consumption based on EV driving cycles available in MATLAB Simulink. The findings of this study will provide insight into the factors that influence EV energy consumption and serve as a guideline in EV powertrain design.

Modular and Scalable Powertrain for Multipurpose Light Electric Vehicles

Light electric vehicles are best suited for city and suburban settings, where top speed and long-distance travel are not the primary concerns. The literature concerning light electric vehicle powertrain design often overlooks the influence of the associated driving missions. Typically, the powertrain is initially parameterized, established, and then evaluated with an ex-post-performance assessment using driving cycles. Nevertheless, to optimize the size and performance of a vehicle according to its intended mission, it is essential to consider the driving cycles right from the outset, in the powertrain design. This paper presents the design of an electric powertrain for multipurpose light electric vehicles, focusing on the motor, battery, and charging requirements. The powertrain design optimization is realized from the first stages by considering the vehicle’s driving missions and operational patterns for multipurpose usage (transporting people or goods) in European urban environments. The proposed powertrain is modular and scalable in terms of the energy capacity of the battery as well as in the electric motor shaft power and torque. Having such a possibility gives one the flexibility to use the powertrain in different combinations for different vehicle categories, from L7 quadricycles to light M1 vehicles.

Model Predictive Control Design and Hardware in the Loop Validation for an Electric Vehicle Powertrain Based on Induction Motors

Electric vehicles (EV) have gained importance in recent years due to environmental pollution and the future scarcity of fossil resources. They have been the subject of study for many years, where much work has focused on batteries and the electric motor (EM). There are several types of motors in the market but the most widely used are induction motors, especially squirrel cage motors. Induction motors have also been extensively studied and, nowadays, there are several control methods used—for example, those based on vector control, such as field-oriented control (FOC) and direct torque control (DTC). Further, at a higher level, such as the speed loop, several types of controllers, such as proportional integral (PI) and model predictive control (MPC), have been tested. This paper shows a comparison between a Continuous Control Set MPC (CCS-MPC) and a conventional PI controller within the FOC method, both in simulation and hardware in the loop (HIL) tests, to control the speed of an induction motor for an EV powered by lithium-ion batteries. The comparison is composed of experiments based on the speed and quality of response and the controllers’ stability. The results are shown graphically and numerically analyzed using performance metrics such as the integral of the absolute error (IAE), where the MPC shows a 50% improvement over the PI in the speed tracking performance. The efficiency of the MPC in battery consumption is also demonstrated, with 5.07 min more driving time.