Performance Analysis of Green Car using Virtual Integrated Development Environment Nak-Tak Jeong, Su-Bin Choi, Choong-Min Jeong, Chao Ma, Jinhyun Park, Sung-Ho Hwang, Hyunsoo Kim and Myung-Won Suh Abstract To evaluate the performance of green car, the virtual integrated development environment which reflects the traffic situations and driving mode is established. The platform of the electric vehicle is developed and the virtual driving environment is constructed. The simulator and GUI are constructed in order to conduct performance test various green cars such as hybrid, electric vehicle. Two electric vehicles are selected in this paper to reflect the driving patterns and mode as an example. The electricity performances of the above vehicles are compared. Keywords Green car, VIDE (Virtual Integrated Development Environment), EV (Electric ), EP (Electricity Performance), Simulator R I. INTRODUCTION ECENTLY, due to various environmental problems and increases of international oil price, demand for automobile rapidly expands to green car that has high performance and high energy efficiency [1]-[3]. Accordingly, various researches are carried out to develop green car such as EV (Electric ), HEV (Hybrid Electric ), PHEV (Plug-in Electric ) and FCEV (Fuel Cell Electric ) [4]-[5]. Not only automakers but manufacturers of automobile parts have an interest and start out developing components of green car such as engine, battery and motor-generator. However, manufacturing companies of vehicle parts have several difficulties on performance tests of full car because they have not sufficient facilities and equipment. Therefore, it is necessary to develop VIDE (Virtual Integrated Development Environment) which can evaluate performance their component in the whole green vehicle. VIDE is a technique that interlocks the virtual driving environment with real-time simulator in order to assess the performance of components. It enables component companies to test performance in design stage for substantial reduction in time and costs of development. Nak-Tak Jeong is with the Graduate School of Mechanical Engineering Sungkyunkwan University 300 Chunchun-dong, Jangan-gu, Suwon, Gyunggi, Korea. (E-mail: yehistory@skku.edu). Corresponding Author, Myung-Won Suh is with the School of Mechanical Engineering Sungkyunkwan University 300 Chunchun-dong, Jangan-gu, Suwon, Gyunggi, Korea. (Phone: +82-31-290-7502; Fax: +82-31-290-5889; e-mail: suhmw@skku.edu). In this study, the performance of green car is evaluated by using VIDE which is still under developing. Virtual driving environment in this paper is composed of the highway mode and the local mode. The platforms of EV1 which is at developmental stage and EV2 which is already in market are modelled so that can be loaded on the simulator. And the vehicle platforms are interlocked with virtual driving environment. Then, EP (Electricity Performance) of each vehicle is evaluated by virtual driving simulation. II. DEVELOPMENT OF EV PLATFORM Electric vehicle EV1 and EV2 are used in virtual driving experiment. The structure of powertrain system of EV is shown in Fig. 1 and component specifications of each vehicle are shown in Table I and Table II. Fig. 1 Powertrain structure of EV As shown in Fig.2, vehicle models are composed using MATLAB/SIMULINK with the above information. After constructing a model, EV1 is compared with the actual vehicle experiment data and the result of simulation. In the case of EV2, it does not have actual vehicle experiment data so it compared the data with the result of simulation using Cruise which is commercial S/W. As shown in Fig.3 and Fig.4, suitability of virtual vehicle platform is verified. 243
TABLE I COMPONENT SPECIFICATIONS OF EV1 EV1 Item Specifications Motor Battery Max output(kw) Max torque(nm) Type Capacity(kwh) Max speed(km/h) Drive range(km) Weight(kg) 50 164.6 Lithium-ion 16.4 130 140 1247 TABLE Ⅱ COMPONENT SPECIFICATIONS OF EV2 EV2 Item Specifications Motor Max output(kw) Max torque(nm) 80 280 Fig. 3 Simulator verification of EV1 Battery Type Capacity(kwh) Max speed(km/h) Drive range(km) Weight(kg) Lithium-ion 24 145 160 1520 Fig. 4 Simulator verification of EV2 Fig. 2 Virtual vehicle model of EV III. VIRTUAL DRIVING ENVIRONMENT The highway from Seoul to Cheon-an and local roads around Cheon-an City are designed as virtual driving environment using Presagis Creator 4.2 and Vega-Prime. The highway mode is the Kyoengbu-highway as in Fig.5 between Seoul tollgate and Cheon-an tollgate. Its total driving distance is 63.9km. The local road in Fig.6 is the 629 local road in between Mt. Kwang-duk service station and Un-am three-way intersection lying from Cheon-an City to Gong-ju City. Its total driving distance is 14km. The Fig.7 and Fig.8 are the pictures of the designed virtual driving environment. Fig. 5 Highway between Seoul and Cheon-an 244
Fig. 6 Local road around Cheon-an V. CONSTRUCTION OF VIRTUAL DRIVING SIMULATOR Virtual driving environment is interlocked with real-time simulator using Presagis Vega-prime 4. Then, GUI display is composed for user convenience as shown in Fig.9. GUI consists largely of four parts. The user can configure the simulation conditions from left to right of the GUI. The part marked 1 on the figure is for selecting the type of green car. The vehicle is provided by the simulator includes EV, HEV, PHEV, and FCEV. The part marked 2 is for selecting the platform of the green car chosen in part 1. To take EV as the example, EV1 or EV2 can be selected. The part marked 3 is for selecting the driving conditions for the vehicle. Operation conditions include FUDS, EUDC, JAPAN 10-15 mode for fuel efficiency evaluation of existing internal combustion engine vehicles, and the mode operating the virtual driving track constructed in chapter 3 in this paper. Finally, the part marked 4 is for the execution of actual simulation and checking the result. Pressing the Open Simulink button brings up the simulator screen of green car constructed with MATLAB/Simulink.And the vehicle simulator is constructed. To be able to drive like actual vehicle, frame is designed and made as shown in Fig.10. Also, seats are disposed and driving device, which are steering wheel, acceleration and brake pedals. Fig. 7 Virtual driving track for the highway mode Fig. 9 GUI display Fig. 8 Virtual driving track for the local road mode IV. ELECTRICITY PERFORMANCE The EP (Electricity Performance) is indicator that evaluates the energy efficiency. It is driving distance with 1kwh electrical energy and the unit is km/kwh, and obtainable through the battery SOC (State Of Charge). EP is calculated as in equation (1). D is driving distance and C is battery capacity. EP = D /[( SOC initial SOC f i nal) C] (1) Fig. 10 Driving simulator 245
TABLE Ⅳ DRIVING EXPERIMENT DATA FOR HIGHWAY MODE velocity(km/h) SOC EP(km/kwh) EV1 100 55.18 7.07 EV2 100 53.60 4.98 on the local road which has more curves than while they are driving on the highway mode. Fig. 11 Conceptual diagram of VIDE composition Total conceptual diagram of VIDE composition is shown in Fig.11. First, the GUI of PC2 is for configuration, based on which the platform provided in this study can be selected. The selected platform can be corrected and the corrected platform is loaded to the real-time simulator through simulation execution. PC1 receives the input of the acceleration, braking, and intent of steering from the driver and uses CAN communication to deliver to the real-time simulation environment. In the real-time simulation environment, the platform configured in PC2 and the data received from PC1 are utilized to calculate the operation characteristics of the current green car, and finally the vehicle status or the component characteristics are outputted through two monitors. VI. VIRTUAL DRIVING EXPERIMENT After construction VIDE, virtual driving experiment is performed. The subjects consisted of 5 men with age around 20 who are healthy and experienced drivers. The subjects have experience with the driving simulator prior to the experiment. The experiment is performed four times for each vehicle and driving mode. The initial battery SOC of each vehicle is 90%. In the local road mode, EP is compared on average velocity 60km/h and 100km/h and in the highway mode EP is compared on only 100km/h because of driving at high speed in highway. EP is calculated through the equation (1). Results of experiment are shown in Table III and Table IV; results are arranged out of average. As results, EV1 showed higher EP than EV2 on both driving mode. Especially, at both the 60km/h and 100km/h, EV1 showed higher EP than EV2 on the local road mode. And at 100km/h, higher EP is showed on highway mode. The reason the local road mode shows lower EP than the highway mode is that driver put on the brake more often while they are driving EV1 EV2 TABLE III DRIVING EXPERIMENT DATA FOR LOCAL ROAD MODE velocity(km/h) 60 100 60 100 SOC 8.43 17.54 10.77 15.57 EP(km/kwh) 10.13 4.87 5.42 3.75 VII. CONCLUSION In this study, virtual driving environment is composed of the highway mode and local road mode. Also, EV platform, real-time simulator and vehicle simulator are constructed. Finally, virtual driving experiment is conducted and performance of EV is evaluated by VIDE. It is expected that VIDE is used to evaluate performance of other types of green car such as HEV, PHEV and FCEV. Accordingly, it is anticipated to be a helpful method which can save time and costs at developmental stage for automakers and subordinate companies.. ACKNOWLEDGMENT This work was financially supported by a Technology Innovation Program grant funded by the Ministry of Knowledge Economy of the Republic of Korea and the Korea Institute for Advancement in Technology through the Workforce Development Program in Strategic Technology. REFERENCES [1] J. H. Park, C. M. Jeong, C. O. Ma, M. W. Suh, H. S. Kim and S. H. Hwang, Development of Real-time Simulation Environment for Performance Analysis of Eco-friendly, Korean Society of Mechanical Engineers spring conference, pp. 47-53, 2012 [2] L. Situ, Electric Development: The past, Present & Future, 3rd International Conference on Power Electronics Systems and Applications, K210509135, 2009. [3] C. H. Park, K. C. Oh, D. H. Kim and H. S. Kim, Operating Strategies of Fuel Cell Hybrid Electric, Korean Society of Automotive Engineers Autumn Conference, pp. 523-528, 2003. [4] C. O. Ma, J. H. Park, S. H. Hwang and H. S. Kim, A Study on Real-Time Based Equivalent Fuel Economy Calculation Algorithm for Green Car, Korean Society of Automotive Engineers spring conference, pp. 1571-1573, 2012. [5] C.O. Ma, J. A. Ji and H. S. Kim, Development of Control Strategy and Energy Management for Plug-in HEV, Korean Society of Automotive Engineers spring conference, pp. 2104-2110, 2011. [6] Y. I. Choi, S. J. Kwon, S. Jang, K. H. Kim, K. Y. Cho and M. W. Suh, A Study on Improving the Reality of the Simulator Based on the Virtual Reality, Journal of the Korean Society of Mechanical Engineers, Vol. A, Vol. 28, No. 8, pp. 1116-1124, 2004 [7] J. H. Song, D. J. Kim, C. H. Lee and C. B. Lee, Simulation of Effect of Driving Pattern on Fuel Economy, Korean Society of Automotive Engineers conference and exhibition, pp. 2039-2044, 2009. [8] M. Ichinose, A. Yokoyama, T. Nishigato, H. Saito, and N. Ueki, Development of Hardware-In-the-Loop Simulator for Adaptive Cruise Control System, Proceedings of the International Symposium on Advanced Control, pp. 207~212, 2002. 246
Nak-Tak Jeong was brought up in Tae-an, Korea on September 30, 1989. He received the B.S. degrees in mechanical engineering from Sungkyunkwan University, Suwon, Korea, in 2013, respectively. He is currently working toward the master course with the graduate school of mechanical engineering, Sungkyunkwan University. His research interests include the virtual driving environment modeling and rendering for vehicle simulator. 247