Transmission For Electric Vehicles Research Articles

Configuration synthesis and screening method for magnetic gear two-speed transmission for electric vehicles

Magnetic field modulated gears have contactless, lubrication-free and highly flexible transmission characteristics, which provide an inherent technological advantage in solving the vibration, jerk and lubrication problems of two-gear transmissions in electric vehicles. To this end, a magnetic gear two-speed transmission drive concept is proposed, and a configuration preference method for two-speed transmissions based on weighted directed topology maps is investigated. A directed weighted graph modulo adjacency matrix and topological evolution rules describing the structure of the system are established. Adjacency matrix ergodic evolution and isomorphism discrimination are investigated for single and two-stage magnetic gear two-speed transmissions, respectively. Through the constructed relative speed link identification algorithm, the speed ratio between any component is calculated quickly. A configuration preference method was established for the defined evaluation objectives via hierarchical analysis. Finally, a prototype was built based on the screening results. The test results showed that the optimal solution could accurately meet the design requirements and realize two-speed transmission. The accuracy of the configuration and screening method of the magnetic gear two-speed transmission system proposed in this article is verified. It provides a theoretical reference for the design of high-performance magnetic gear two-speed transmission.

Development of a gearbox test rig to evaluate the impact of oil formulations on churning and friction losses

From large industrial to small high-speed transmission for electric vehicles, there is a growing interest in reducing the power losses on gearboxes. Hydrodynamic losses are especially relevant on high-speed gearboxes. On electric cars, the gearbox lubricant also works as a cooling fluid for the motor, which brings new challenges as performance under an electrified environment, thermal and electrical conductivity, corrosion protection etc. Most current test rigs use the torque difference between gearbox output and input to calculate the power losses. This work, uses the instantaneous deceleration on a small gearbox to obtain the no-load depending on power losses. Due to its simplicity, the proposed method has the potential to be applied to actual transmissions with very simple sensors and without the need for significant intervention on the actual equipment. The experimental results showed increased churning power losses with the immersion depth and oil viscosity. With the tested transmission oils, the churning losses showed to depend on rotational speed by a power of three, as predicted by the ISO model. The influence of oil viscosity was less evident. Reducing viscosity 2.5 times showed only around 25% reduction in the calculated churning losses. In opposition to the tested transmission oils, a low-viscosity oil with Friction Modifier additives reduced the power losses with the consecutive larger volumes of sump oil, such unexpected result can be explained by the beneficial effect of the oil FM additives.

Deep learning-based electric vehicle transmission system speed ratio prediction research

Deep learning-based electric vehicle transmission system speed ratio prediction research

The effects of alternating current (AC) electrification on the tribological performance of gear materials with internal combustion engine (ICE) and electric vehicle (EV) transmission lubricants

The effects of alternating current (AC) electrification on the tribological performance of gear materials with internal combustion engine (ICE) and electric vehicle (EV) transmission lubricants

High-Speed and Low-Noise Gear Finishing by Gear Grinding and Honing: A Review

AbstractGears are important mechanical parts for transmitting power and play an increasingly important role in the machinery industry. The electric vehicle industry developed rapidly and became a vital development field of the automotive industry over the past few years. The conversion of energy increases the requirements for electric vehicle transmissions, which promotes the development of high-speed and low-noise transmission gear. This paper elaborates on the research progress of high-speed and low-noise gear finishing methods. Firstly, this review analyses the machining requirements, finishing, and specific machining technologies of high-speed and low-noise gears. The importance of gear grinding and honing in high-speed and low-noise gear machining is highlighted. Secondly, the applications of gear grinding and honing in gear modification, error compensation, and texture control are analyzed. Furthermore, the role of precision machining technology in improving gear performance is clarified. Finally, the design and processing methods of the modified tooth flank for gear modification are summarized. In addition, the influence of tooth surface texture on noise is described, and the texture change methods are explored. The well-known open problems of gear finishing are finally identified, and some new research interests are also pointed out. This review will provide valuable references for further research on gear finishing.

Dynamic analysis of two-stage steering reducer for electric vehicle based on ROMAX

Abstract. With the rapid development of electric vehicles in the modern market, the efficiency and performance requirements of electric vehicle transmission systems are getting higher and higher. As an important part of the electric vehicle reducer, the steering reducer can make full use of the advantages of the two-stage deceleration transmission, achieve more efficient power transmission, and improve the acceleration performance and driving performance of electric vehicles. This paper aims to design a two-stage steering reducer for an electric vehicle, which adopts planetary gear transmission type. Firstly, the working principle of the electric vehicle steering reducer is analyzed, and the overall design scheme of the reducer is drawn up. Secondly, the transmission system parameters of the reducer are designed and calculated, including transmission ratio distribution, tooth number ratio calculation, etc. Secondly, the transmission structure of the reducer is designed, including input shaft, output shaft, first planetary gear train, second planetary gear train, reducer shell, bearing, etc., and the reducer model is drawn by three-dimensional software Solidworks. Finally, the strength and deformation check analysis of the two-stage reducer is carried out by using the finite element software ROMAX to evaluate the performance of the designed reducer under this working condition. The full text design has a certain reference, and can be applied to other electric vehicle reducer design to provide theoretical guidance.

Comparative analysis and optimization of nonlinear hysteresis models for a magnetorheological fluid dual-clutch of an electric vehicle transmission

Comparative analysis and optimization of nonlinear hysteresis models for a magnetorheological fluid dual-clutch of an electric vehicle transmission

Solar Based Wireless Power Transmission for Electric vehicle Charging Station

Wireless power transfer (WPT) using magnetic resonance is the technology which could set human free from the annoying wires. In fact, the WPT adopts the same basic theory which has already been developed for at least 30 years with the term inductive power transfer. WPT technology is developing rapidly in recent years. At kilowatts power level, the transfer distance increases from several millimetres to several hundred millimetres with a grid to load efficiency above 90%. The advances make the WPT very attractive to the electric vehicle (EV) charging applications in both stationary and dynamic charging scenarios. For energy, environment, and many other reasons, the electrification for transportation has been carrying out for many years. In railway systems, the electric locomotives have already been well developed for many years. A train runs on a fixed track. It is easy to get electric power from a conductor rail using pantograph sliders. However, for electric vehicles (EVs), the high flexibility makes it not easy to get power in a similar way. Instead, a high power and large capacity battery pack is usually equipped as an energy storage unit to make an EV to operate for a satisfactory distance. The problem for an electric vehicle is nothing else but the electricity storage technology, which requires a battery which is the bottleneck today due to its unsatisfactory energy density, limited lifetime and high cost. Keywords: Wireless Power transfer, Electric Vehicle, Battery

Dual-Transformer-Based DAB Converter With Asymmetrical Power Transmission and High-Power Density for Electric Vehicles

Dual-Transformer-Based DAB Converter With Asymmetrical Power Transmission and High-Power Density for Electric Vehicles

The Effects of the Lubricant Properties and Surface Finish Characteristics on the Tribology of High-Speed Gears for EV Transmissions

Electric vehicle (EV) transmissions operate at high speeds. High-speed operation puts higher demands on bearings, seals, and gears. Bearings in EV transmissions are prone to electrically induced bearing damage and may exhibit signs of pitting and fluting. Surface-initiated rolling contact fatigue is another common problem gaining increased attention lately. Most EV transmissions require a coupling between an oil-lubricated gearbox to an electrical motor that runs with minimal lubrication at very high rpm. The high mechanical and thermal stresses the seals are exposed to under starved lubrication conditions have a detrimental impact on their service life. Hence, proper lubrication is critical. In general, EV transmission fluids call for a somewhat different spectrum of properties compared to conventional ATFs. Gear tribology simulations open new ways to the design and optimization of lubrication for EV transmissions. Additionally, such simulations can also provide valuable insights into the effects of different oil properties on cooling and lubrication efficiencies, thereby helping in matching the lubricant and hardware characteristics for optimal performance. In the present communication, we demonstrate the effects of different lubricants and surface finishing technologies on the tribology of high-speed gears using tribological tests and advanced thermal elastohydrodynamic (TEHD) simulations. The important roles of lubricity additives and surface finish optimization are highlighted in conjunction with a move towards ultralow viscosity EV transmission fluids.

Optimal Gear Shift Control of Two-Speed Dual-Clutch Transmission in Electric Vehicle for Smoothness and Friction Loss Reduction

Optimal Gear Shift Control of Two-Speed Dual-Clutch Transmission in Electric Vehicle for Smoothness and Friction Loss Reduction

Drive-Cycle-Based Configuration Design and Energy Efficiency Analysis of Dual-Motor 4WD System With Two-Speed Transmission for Electric Vehicles

The development of energy-saving technology is important to the promotion of electric vehicles. In the design process of electric vehicles, the drive configuration is generally determined first, and then the energy management strategy is studied. However, this process doesn’t design the drive configuration with higher energy saving potential from the economic perspective of vehicle driving conditions, but directly determines the drive configuration. So, in this paper, the characteristics of the vehicle’s driving conditions are analyzed firstly, and then based on the analysis results, a new dual-motor 4WD EV configuration with higher energy saving potential is proposed, which only has a two-speed transmission in the rear axle. Then the parameters of the proposed driving configuration are calculated to meet the vehicle dynamic or economic needs of various driving conditions. Then an energy management strategy is developed for the judgement of optimal torque distribution of the front and rear axle motors and gear shifting logic. Finally, the comparison simulations are conducted and the results show that, in WLTC, DM-2ST can reduce vehicle energy consumption by 9.13% and 4.84% respectively compared to DM-FTD and DM-OTD. In UDDS, DM-2ST can reduce vehicle energy consumption by 11.04% and 5.77% respectively compared to DM-FTD and DM-OTD.

Development of Shift Map for Electric Commercial Vehicle and Comparison Verification of Pneumatic 4-Speed AMT and 4-Speed Transmission with Synchronizer in Simulation

As the automotive industry transitions from internal combustion engine vehicles to the era of electric cars, extensive research is being conducted in the field of electric vehicles. While a significant portion of this research focuses on the electrification of passenger cars, commercial vehicles have experienced relatively modest changes towards electric propulsion. Particularly, challenges related to power and efficiency have prompted a concentrated effort in addressing these issues. However, improvements in the efficiency of motors and inverters are reaching their limits, necessitating the development of multi-speed transmissions for electric commercial vehicles to enhance overall system efficiency. In this paper, the development of a 4-speed transmission with a synchronizer designed for electric commercial vehicles is presented as part of a project. A transmission shift map was developed, and verification of increased power and efficiency was conducted through a comparison with the existing product (a pneumatic 4-speed internal combustion engine transmission) installed in the target commercial vehicle. The study utilized vehicle dynamics, component modeling, and simulation environments to assess the improvements in performance.

Tribological behavior of electric vehicle transmission oils using Al2O3 nanoadditives

Antifriction and antiwear performances of Al2O3 nanoparticles (NPs) as additives of an automatic transmission fluid, ATF, are presented in this research. For this purpose, four nanodispersions were formulated: ATF + 0.05 wt% Al2O3 NPs, ATF + 0.10 wt% Al2O3 NPs, ATF + 0.15 wt% Al2O3 NPs and ATF + 0.20 wt% Al2O3 NPs to identify the optimal concentration of additive. Tribological experiments were taken at pure sliding conditions, with the formulated nanolubricants and the ATF, under a working load of 20 N. The four nanolubricants tested resulted in lower friction coefficients than those obtained using ATF, reaching a maximum reduction of 6 % with the ATF + 0.10 wt% Al2O3 nanolubricant. The tribological pairs tested with the Al2O3 nanolubricants show lower wear than those tested with the ATF, having the best wear decrease with the ATF + 0.10 wt% Al2O3 nanolubricant, with reductions of 45, 57 and 78 %, respectively, in diameter, depth and area of the wear scar. Furthermore, by means of confocal Raman microscopy, roughness evaluation and SEM-EDX of the worn tribological specimens, it can be determined that mending, tribo-sintering as well as rolling mechanisms occur.

Gear error control and response of electric vehicle transmission gearing based on gear trimming

The lightweight development of electric vehicle motors is a prominent future trend, with the challenge of transmission vibration and noise acting as a key bottleneck that limits the enhancement of power and speed in electric vehicle drive systems. The noise generated by electric vehicle transmissions is primarily associated with the transmission system and gear structure. In line with this, the present study proposes an analysis of transmission error and response mechanisms through gear modifications. The research delves into the analysis of gear deformation and error generation characteristics. It further investigates methods for parametric equation modeling, tooth profile modification, deformation imprint analysis, and vibration response modeling to examine excitation response analysis and noise reduction techniques pertaining to transmission errors. The findings demonstrate that, under 40 % torque, the shaped gear exhibited a maximum reduction in transmission error of 34.2 %, resulting in an overall error improvement of over 5.7 %. Moreover, the maximum error difference after tooth profile and tooth direction shaping exceeded 2 %. The gear-shaping-based electric vehicle transmission showcased favorable economic and technical performance, while its excitation response mechanism provided valuable guidance for mass production. Overall, these results highlight the significance of analyzing transmission errors through gear modifications in achieving lightweight electric vehicle motors. By addressing transmission vibration and noise issues, this research contributes to overcoming limitations and promoting advancements in power and speed within electric vehicle drive systems.

Two-Speed Transmission Structure and Optimization Design for Electric Vehicles

The trend in the global automotive industry is moving towards electric vehicles that do not emit exhaust gases and use eco-friendly fuel. Electric vehicles are more eco-friendly compared to internal combustion engine vehicles, as they emit less carbon dioxide and pollutants. Research and development are actively underway to produce new electric vehicle models in the rapidly growing electric car market. In this study, a 2-speed transmission for electric vehicles, applicable to 300 Nm-class electric cars, has been developed. The 2-speed transmission structure enables efficient energy use and utilizes a planetary gear set and wet multi-plate clutch, which are effective in the power transmission process. The 2-speed transmission developed through the research results of this paper has a compact structure optimized for electric vehicles. The design feasibility of the transmission was verified through performance tests of the prototype, contributing to fuel efficiency improvement and environmental enhancement.

Transmission for Hybrid and Electric Vehicles

Transmission for Hybrid and Electric Vehicles

Diamond like-carbon coatings for electric vehicle transmission efficiency

A barrier to the adoption of battery electric vehicles is consumer range anxiety. This paper investigates the driving range conceded as a result of the parasitic frictional losses incurred at the gear mesh in a two-stage battery electric vehicle transmission. Amelioration of the parasitic losses through changes to surface roughness and application of thin wear resistant coatings such as DLC are considered. The tribo-dynamics model of the gear frictional losses includes topographical structure of the respective surfaces characterised through surface specific fractal parameters. Analysis shows that the use of the investigated amorphous hydrogenated undoped DLC coating could potentially save 1.1 km of vehicle range during extra urban driving and 0.9 km under urban driving over a full battery discharge cycle.

Parameter Optimization and Control Strategy of Hybrid Electric Vehicle Transmission System based on Improved GA Algorithm

Most of the traditional hybrid electric vehicles (HEVs) choose to optimize the transmission ratio parameters, and the parameter changes of the whole vehicle and other components are only calculated as fixed values. It is difficult to give consideration to the optimization of the economy and power of hybrid vehicles. Therefore, the research proposes to build the transmission ratio, the required power of the vehicle’s working mode, and other models through the dynamic analysis. The parameters of the whole vehicle are optimized on the basis of parameter matching. At the same time, this paper chooses to adopt a hybrid optimization algorithm, combining particle swarm optimization (PSO) and genetic algorithm (GA). The weighted average method and constraint method are used to design the fitness function. The simulation experiment is carried out by Cruise software and MATLAB. Compare the iterative fitness of the PSO-GA algorithm with the traditional PSO and GA algorithm. It can be concluded that PSO-GA converges at the 12th iteration, with an average optimal fitness of 0.5239, which is higher than the traditional algorithm. At the same time, the parameter optimization of PSO-GA and the simulated annealing algorithm is compared. It is found that in the same task, the gasoline consumption after SA algorithm optimization is 0.561 L, while the fuel consumption under PSO-GA algorithm optimization is 0.475 L. The method proposed in this study has improved the power and economy of the HEV model and is effective.

Optimization of multi-speed transmission for electric vehicles based on electrical and mechanical efficiency analysis

Multi-speed transmissions for electric vehicles (EVs) can better improve EV efficiency and performance in comparison with conventional single-speed transmissions. To achieve a superior multi-speed transmission design, gear ratios and shifting patterns should be optimized by considering the electrical and mechanical efficiencies. Because most powertrain losses occur in the inverter, motor, and transmission, loss analysis was conducted according to the characteristics of each component. To confirm the effects of these component efficiencies on EVs, an EV efficiency analysis was performed based on three cases of powertrain efficiency by considering the variable efficiency of each component combination: i) motor only, ii) motor and transmission, and iii) inverter, motor, and transmission. An optimization problem was formulated by adopting design variables, such as gear ratios and shifting patterns, and the objectives of energy consumption and acceleration ability. An artificial neural network (ANN)-based multi-objective optimization process was proposed as an alternative to the excessive effort for calculation in the optimization process. To verify the importance of considering the efficiency of various powertrain components, transmission optimization was performed for the variable efficiency of each component combination. When comparing the highest efficiency solutions of the cases considering only part of component efficiency with the case considering all components, the energy consumption and acceleration ability of the latter case were found to be superior by approximately 1.7% and 5.1%, respectively. Furthermore, since the computational time for the EV and ANN models required approximately nine months and one day, respectively, this result demonstrates the effectiveness of the ANN-based multi-objective optimization process.