scholarly journals Torque Optimal Allocation Strategy of All-Wheel Drive Electric Vehicle Based on Difference of Efficiency Characteristics between Axis Motors

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1122 ◽  
Author(s):  
Xiaogang Wu ◽  
Dianyu Zheng ◽  
Tianze Wang ◽  
Jiuyu Du
Keyword(s):  
Energy Consumption ◽  
Power System ◽  
Electric Vehicle ◽  
Driving Cycle ◽  
Drive Power ◽  
Distribution Method ◽  
Torque Distribution ◽  
Wheel Drive ◽  
Average Distribution ◽  
The Difference

All-wheel drive is an important technical direction for the future development of pure electric vehicles. The difference in the efficiency distribution of the shaft motor caused by the optimal load matching and motor manufacturing process, the traditional torque average distribution strategy is not applicable to the torque distribution of the all-wheel drive power system. Aiming at the above problems, this paper takes the energy efficiency of power system as the optimization goal, proposes a dynamic allocation method to realize the torque distribution of electric vehicle all-wheel drive power system, and analyzes and verifies the adaptability of this optimization algorithm in different urban passenger vehicle working cycles. The simulation results show that, compared with the torque average distribution method, the proposed method can effectively solve the problem that the difference of the efficiency distribution of the two shaft motors in the power system affects the energy consumption of the power system. The energy consumption rate of the proposed method is reduced by 5.96% and 5.69%, respectively, compared with the average distribution method under the China urban passenger driving cycle and the Harbin urban passenger driving cycle.

Developing an electric vehicle urban driving cycle to study differences in energy consumption

2018 ◽  
Vol 26 (14) ◽  
pp. 13839-13853 ◽  
Author(s):  
Xuan Zhao ◽  
Jian Ma ◽  
Shu Wang ◽  
Yiming Ye ◽  
Yan Wu ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Driving Cycle

scholarly journals Annual Variation in Energy Consumption of an Electric Vehicle Used for Commuting

Energies ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 4639 ◽  
Author(s):  
Anatole Desreveaux ◽  
Alain Bouscayrol ◽  
Elodie Castex ◽  
Rochdi Trigui ◽  
Eric Hittinger ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Experimental Measurement ◽  
Air Conditioning ◽  
Annual Variation ◽  
Accurate Determination ◽  
Driving Cycle ◽  
Simulation Tool ◽  
Real Vehicle

The energy consumption of an electric vehicle is primarily due to the traction subsystem and the comfort subsystem. For a regular trip, the traction energy can be relatively constant but the comfort energy has variation depending on seasonal temperatures. In order to plan the annual charging operation of an eco-campus, a simulation tool is developed for an accurate determination of the consumption of an electric vehicle throughout year. The developed model has been validated by comparison with experimental measurement of a real vehicle on a real driving cycle. Different commuting trips are analyzed over a complete year. For the considered city in France (Lille), the comfort energy consumption has an overconsumption up to 33% in winter due to heating, and only 15% in summer due to air conditioning. The urban commuting driving cycle is more affected by the comfort subsystem than extra-urban trips.

scholarly journals Optimal Control for Hybrid Energy Storage Electric Vehicle to Achieve Energy Saving Using Dynamic Programming Approach

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 588 ◽  
Author(s):  
Chaofeng Pan ◽  
Yanyan Liang ◽  
Long Chen ◽  
Liao Chen
Keyword(s):  
Dynamic Programming ◽  
Energy Consumption ◽  
Power System ◽  
Energy Saving ◽  
Electric Vehicle ◽  
System Efficiency ◽  
Rule Based ◽  
Hybrid Power System ◽  
Hybrid Power ◽  
Simulation Results

In this paper, the efficiency characteristics of battery, super capacitor (SC), direct current (DC)-DC converter and electric motor in a hybrid power system of an electric vehicle (EV) are analyzed. In addition, the optimal efficiency model of the hybrid power system is proposed based on the hybrid power system component’s models. A rule-based strategy is then proposed based on the projection partition of composite power system efficiency, so it has strong adaptive adjustment ability. Additionally. the simulation results under the New European Driving Cycle (NEDC) condition show that the efficiency of rule-based strategy is higher than that of single power system. Furthermore, in order to explore the maximum energy-saving potential of hybrid power electric vehicles, a dynamic programming (DP) optimization method is proposed on the basis of the establishment of the whole hybrid power system, which takes into account various energy consumption factors of the whole system. Compared to the battery-only EV based on simulation results, the hybrid power system controlled by rule-based strategy can decrease energy consumption by 13.4% in line with the NEDC condition, while the power-split strategy derived from the DP approach can reduce energy consumption by 17.6%. The results show that compared with rule-based strategy, the optimized DP strategy has higher system efficiency and lower energy consumption.

scholarly journals On the Comparison of 2- and 4-Wheel-Drive Electric Vehicle Layouts with Central Motors and Single- and 2-Speed Transmission Systems

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3328 ◽  
Author(s):  
Stefano De Pinto ◽  
Pablo Camocardi ◽  
Christoforos Chatzikomis ◽  
Aldo Sorniotti ◽  
Francesco Bottiglione ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Operating Efficiency ◽  
Urban Mobility ◽  
Transmission Systems ◽  
Torque Distribution ◽  
Driving Cycles ◽  
Wheel Drive ◽  
Road Friction ◽  
Optimization Routine

Electric vehicles (EVs) are characterized by a significant variety of possible powertrain configurations, ranging from one to four electric machines, which can have an on-board or in-wheel layout. Multiple models of production EVs have recently been introduced on the market, with 4-wheel-drive (4WD) architectures based on a central motor within each axle, connected to the wheels through a gearbox, a differential, and half-shafts. In parallel, an important body of research and industrial demonstrations have covered the topic of 2-speed transmission systems for EVs, with the target of enhancing longitudinal acceleration and gradeability performance, while increasing the operating efficiency of the electric powertrain. Although several recent studies compare different electric powertrain architectures, to the best of the authors’ knowledge the literature misses a comparison between 2-wheel-drive (2WD) and 4WD configurations for the same EV, from the viewpoint of drivability and energy consumption. This paper targets this gap, by assessing 2WD and 4WD powertrain layouts with central motors, for a case study light passenger car for urban mobility, including consideration of the effect of single- and 2-speed transmission systems. An optimization routine is used to calculate the energy-efficient gear state and/or torque distribution for each considered configuration. For the specific EV, the results highlight the favourable trade-off of the single-speed 4WD layout, capable of reducing the energy consumption during driving cycles by approximately 9% with respect to the conventional 2WD layout with single-speed transmission, while providing satisfactory drivability and good gradeability, especially in low tire–road friction conditions.

Model-Based Design and Evaluation of Electric Vehicle Powertrain With Independent Driving Motors

2015 ◽  
Author(s):  
Haotian Wu ◽  
Haiyan Zhang
Keyword(s):  
Energy Consumption ◽  
Vector Control ◽  
Electric Vehicle ◽  
Torque Vector ◽  
Model Based ◽  
Transfer Case ◽  
Wheel Drive ◽  
Battery Capacity ◽  
Evaluation Approaches ◽  
Case Based

The transfer case based all-wheel drive electric vehicle (TCAWDEV) and dual-axle AWDEV have been investigated to balance concerns about energy consumption, drivability and stability of vehicles. An ideal AWDEV (IAWDEV) powertrain architecture is proposed by this research; the architecture has an independent driving motor at each wheel; in essence, the IAWDEV is a distributed powertrain that provides various combinations of torque vector control. This research also investigated the simplified methods to estimate the battery capacity and the operation envelope of motors, and employed model-based evaluation approaches to recursively identify the proper powertrain components. The model-based evaluation was conducted in LMS AMESim. The results show that the IAWDEV could reduce the complexity of drivetrain, and also can harvest more braking energy under poor road contact.

scholarly journals All-Wheel-Drive Torque Distribution Strategy for Electric Vehicle Optimal Efficiency Considering Tire Slip

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 25245-25257
Author(s):  
Kaibin Cao ◽  
Minghui Hu ◽  
Dongyang Wang ◽  
Shuaipeng Qiao ◽  
Cong Guo ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Torque Distribution ◽  
Drive Torque ◽  
Distribution Strategy ◽  
Wheel Drive ◽  
Optimal Efficiency

scholarly journals Adaptive Driving Cycles of EVs for Reducing Energy Consumption

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2592
Author(s):  
Iwona Komorska ◽  
Andrzej Puchalski ◽  
Andrzej Niewczas ◽  
Marcin Ślęzak ◽  
Tomasz Szczepański
Keyword(s):  
Energy Consumption ◽  
Electric Vehicle ◽  
Traffic Engineering ◽  
Traffic Management ◽  
Gaussian Process Regression ◽  
Road Transport ◽  
Driving Cycle ◽  
Virtual Design ◽  
Driving Cycles ◽  
Drive Systems

A driving cycle is a time series of a vehicle’s speed, reflecting its movement in real road conditions. In addition to certification and comparative research, driving cycles are used in the virtual design of drive systems and embedded control algorithms, traffic management and intelligent road transport (traffic engineering). This study aimed to develop an adaptive driving cycle for a known route to optimize the energy consumption of an electric vehicle and improve the driving range. A novel distance-based adaptive driving cycle method was developed. The proposed algorithm uses the segmentation and iterative synthesis procedures of Markov chains. Energy consumption during driving is monitored on an ongoing basis using Gaussian process regression, and speed and acceleration are corrected adaptively to maintain the planned energy consumption. This paper presents the results of studies of simulated driving cycles and the performance of the algorithm when applied to the real recorded driving cycles of an electric vehicle.

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