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Yin A.,Hefei University of Technology | Zhao H.,Hefei University of Technology | Zhou B.,Hefei University of Technology | Jiang H.,Hefei University of Technology | Lu R.,Society of Automotive Engineers of China
Qiche Gongcheng/Automotive Engineering

In this paper, a driving cycle identification method is adopted, which combines principal component analysis with fuzzy clustering, to estimate the driving range of battery electric vehicle. Firstly twenty representative driving cycle data are selected and divided into 215 cycle segments, and 12 characteristic parameters are chosen to conduct principal component analysis, fuzzy C-means clustering and driving cycle identification. Then a model for battery electric vehicle is established with MATLAB/Simulink to perform driving cycle identification and the simulation estimations of vehicle energy consumption and driving range. Finally a real vehicle validation test is carried out on drum test bench with ECE15 cycle. The results show that compared with test data, the maximum absolute error of simulated estimates is 1.905km, and the corresponding average absolute error and relative error are 0.742km and less than 3% respectively. ©, 2014, Qiche Gongcheng/Automotive Engineering. All right reserved. Source

Wang C.-Y.,Control Iron and Steel Research Institute, China | Wang C.-Y.,Taiyuan Iron and Steel Group Ltd | Chang Y.,Dalian University of Technology | Yang J.,Society of Automotive Engineers of China | And 3 more authors.
Journal of Iron and Steel Research International

Both microstructure and mechanical properties of low alloy steels treated by quenching and partitioning (Q&P) process were examined. The mixed microstructure of martensite and large-fractioned retained austenite (about 27.3 %) was characterized and analyzed, excellent combinations of total elongation of 19 % and tensile strength of 1835 MPa were obtained, and three-stage work hardening behavior was demonstrated during tensile test. The enhanced mechanical properties and work hardening behavior were explained based on the transformation-induced plasticity effect of large-fractioned austenite. © 2016 Central Iron and Steel Research Institute. Source

Yin A.,Hefei University of Technology | Yin A.,China Automotive Technology and Research Center | Zhao H.,Hefei University of Technology | Zhao H.,China Automotive Technology and Research Center | And 3 more authors.
Qiche Gongcheng/Automotive Engineering

Based on hybrid system theory, the powertrain system of a hybrid electric vehicle (HEV) with rear wheel drive is analyzed, a control model for HEV powertrain system is built based on hybrid automaton model, and a mode-switch-based drive control strategy and a regenerative braking control strategy with braking force coordination control are proposed. Then a simulation model for HEV powertrain control strategy is set up with Simulink/Stateflow hybrid modeling method, and both performance simulation and road test on a real sample HEV are conducted. The results show that the performance of real sample HEV meets the design requirements with its fuel consumption 15.9% less than the traditional vehicle of same category under the typical urban driving cycles in China. © 2015, Society of Automotive Engineers of China. All right reserved. Source

Yin A.,Hefei University of Technology | Chen W.,Hefei University of Technology | Zhao H.,Hefei University of Technology | Lu R.,Society of Automotive Engineers of China | Feng R.,Hefei University of Technology
Qiche Gongcheng/Automotive Engineering

A simulation model for the power-train of a ISG HEV is established using CRUISE software. An optimization on the gear ratio parameters of power-train is performed by adopting fast elitist non-dominated sorting genetic algorithm (NSGA-II) with acceleration time and fuel consumption as objectives. The results show that after optimization the fuel consumption of vehicle with NEDC cycle reduces by 7.05% on the premise of meeting the design specifications of vehicle power performance. Source

Lu H.,East China University of Science and Technology | Lu H.,CITIC Metal Co. | Wang Z.,Society of Automotive Engineers of China | Mingtu M.,China Automotive Engineering Research Institute | And 2 more authors.
Lecture Notes in Electrical Engineering

Based on the multi-objective optimization and design of automotive body, the evaluation method of automotive lightweight is studied. An innovative evaluation method and the automotive lightweight comprehensive evaluation index E are presented, which is expressed by following formula E = m body/Ct × A × [ENCAP] × F [kg/Nm/ o × m2 × Hz × 104], and the weight of car body is associated with the model, stiffness of car body and safety of cars by this formula. The relationship between automotive lightweight and correlative functions is discussed. The evaluation method is confirmed by applying the data of 14 typical passenger cars. The relationship between evaluation index E and relational parameters are discussed, and some comparison and analysis are carried out, the sensitivity of E value for varying of relational parameters values is demonstrated, and the sensitivity is acceptable. And according to the E value, the lightweight level of a car can be defined, which is from 1 to 5 stars. A requirement of integrated fuel consumption for lightweight star level based on car mass is presented to be as a modifier to modify the final star-rating results of a car. This evaluation regulation considers the modal, stiffness, and sizes of car body, and safety of cars, and fuel consumption which are associated with weight of car body and car mass. A conclusion is attained that the evaluation method of lightweight presented by this paper is feasible, however, the details of evaluation regulation of automotive lightweight will be studied further, and an official new car evaluation regulation of automotive lightweight will be presented. According to the evaluation results and stars rating, customers can choose to buy a more lightweight and energy-saving car. And based on the stars rating, governments can also improve energy saving and emission reduction of automotive industry, by encouraging the car makers which produce the lightweight cars. © Springer-Verlag 2013. Source

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