• International Journal of Technology (IJTech)
  • Vol 13, No 4 (2022)

Power Requirement and Cost Analysis of Electric Bus using Simulation Method with RCAVe-EV1 Software and GPS Data; A Case Study of Greater Jakarta

Power Requirement and Cost Analysis of Electric Bus using Simulation Method with RCAVe-EV1 Software and GPS Data; A Case Study of Greater Jakarta

Title: Power Requirement and Cost Analysis of Electric Bus using Simulation Method with RCAVe-EV1 Software and GPS Data; A Case Study of Greater Jakarta
Hendri D S Budiono, Ghany Heryana, Mohammad Adhitya, Danardono Agus Sumarsono, Nazaruddin, Rolan Siregar, Estiko Rijanto, Bayu D Aprianto

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Cite this article as:
Budiono, H.D.S., Heryana, G., Adhitya, M., Sumarsono, D.A., Nazaruddin, Siregar, R., Rijanto, E., Aprianto, B.D., 2022. Power Requirement and Cost Analysis of Electric Bus using Simulation Method with RCAVe-EV1 Software and GPS Data; A Case Study of Greater Jakarta. International Journal of Technology. Volume 13(4), pp. 793-802

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Hendri D S Budiono Research Center for Advanced Vehicles (RCAVe), Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Jawa Barat 16424, Indonesia
Ghany Heryana 1. Research Center for Advanced Vehicles (RCAVe), Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Jawa Barat 16424, Indonesia 2. Mechanical Engineering Department, Sekolah Tinggi Tekn
Mohammad Adhitya Research Center for Advanced Vehicles (RCAVe), Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Jawa Barat 16424, Indonesia
Danardono Agus Sumarsono Research Center for Advanced Vehicles (RCAVe), Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Jawa Barat 16424, Indonesia
Nazaruddin Research Center for Advanced Vehicles (RCAVe), Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Jawa Barat 16424, Indonesia
Rolan Siregar 3Research Center for Smart Mechatronics, National Reseacrh and Innovation Agency, Bandung, Jawa Barat, Indonesia
Estiko Rijanto Research Center for Smart Mechatronics, National Reseacrh and Innovation Agency, Bandung, Jawa Barat, Indonesia
Bayu D Aprianto Research Center for Advanced Vehicles (RCAVe), Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Jawa Barat 16424, Indonesia
Email to Corresponding Author

Abstract
Power Requirement and Cost Analysis of Electric Bus using Simulation Method with RCAVe-EV1 Software and GPS Data; A Case Study of Greater Jakarta

Electric vehicles’ power requirement and cost analysis require consideration in terms of their usage load and mileage. It is due to the unique character of the charging energy compared to internal combustion vehicles. The motor capacity and mileage will affect the vehicle's weight, especially the battery. If the battery is excessively big, it will affect passenger space. In comparison, buses with diesel engines are generally designed for long distances and rough roads. If used in the city, with relatively gentle road types, the engine will tend to be over-specification. This research aims to design the bus power requirements according to road conditions. The method is theoretical and simulated with specific GPS data. In this case, the bus power is designed for the city's needs, with a case study of battery electric buses (BEBs) for the route of the city of Jakarta and its surroundings, namely Bogor, Depok, Tangerang, and Bekasi. In addition, an economic study will also be a part of this research. Bus companies need this study to decide on the procurement and use of an electric bus fleet. The simulation results show that the power and battery capacity of inner-city buses need not be as large as inter-city buses. A bus with a motor power rating of 100 kW and batteries with a total of 200 kWh is very appropriate to carry 85 passengers over a distance of 200 km on one charge. Moreover, with proper incentives from the government, the price of electric inner-city buses is very competitive. It has the advantage of having a service life of more than ten years.

BEBs; Cost analysis; Electric bus fleet; EV; Power requirement

Introduction

Because decision-makers depend on the findings, bus fleet design is fascinating for researchers. Inner buses have become one of the targets to be used as electric buses because the population in the city is expected to replace many private vehicles. Inner buses can achieve the target of clean air in the city and town to become comfortable to live in or become a place for healthy activities (Adheesh et al., 2016). However, the transition from the diesel bus era to the electric bus was not free from problems. It has been discussed and described in research conducted in Italy (Pelletier et al., 2019).

The discussion of this bus design is generally to overcome the time required for charging the battery. The fast-charging strategy is one option, but a short stop time is not enough for the fast charger to charge the battery adequately. Other strategies, such as swapping, are also possible alternatives, although later infrastructure will be needed, especially for buses' battery withdrawal mechanism and installation. In the end of it is the costs of charging station infrastructure. The results suggest:

·      The service frequency, circulation length, and operating speed of a transit system;

·      Charging lanes enabled by currently available inductive wireless charging technology;

·      Swapping stations;

·      Charging stations are cost-competitive only for transit systems with shallow service frequency and short circulation; and

·      Reduce their unit-length construction cost or enhance their charging power (Chen et al., 2018).

Fast charging is a good solution, but it requires charging station infrastructure and good battery life (Ding et al., 2015). The wireless charging method has also been developed to reduce the plug-in and plug-out time of the charger cable. This induction charging requires environmental conditions and the precision of the bus position when at the bus stop or charging station (Bi et al., 2015). Uncertainty in demand and bus utility must be addressed. It is much more complex than handling buses with diesel engines, where these buses do not have much problem with the distance and the presence of a gas station. However, bus lanes must be appropriately designed on electric buses, and drivers must be disciplined to pass through predetermined routes. Otherwise, the risk of running out of energy and not finding a charging station and a long queue of charging stations will be a big problem (Teoh et al., 2018). Again, the battery must be considered in the design of the charging station infrastructure. The deployment of charging infrastructures and the number of standby buses available significantly affect the operational efficiency of electric bus systems. This work has developed a stochastic integer program to jointly optimize charging station locations and bus fleet size under random bus charging demand, considering time-of-use electricity tariffs (An, 2020).

      The mileage concern was also overcome by the design of the hybrid bus. Thus, there are two types of propulsion on the bus. It is not much different from creating a small hybrid vehicle or sedan. With this design, the mileage becomes more flexible. However, the targets for obtaining energy and a cleaner environment have not been achieved. Thus, the hybrid bus is not the best solution in this case. This research was  carried out at the beginning of the era of electric vehicles being touted (Xiong et al., 2009). For particular needs, hybrid buses may be needed. Therefore, research on this matter also remains strategic. Optimizing energy use on hybrid buses is done by creating a dynamic power management program (Peng et al., 2017).

     Research with a case study in Penghu seeks to reduce the construction costs of plug-in electric buses. In this study, extensive analysis has been done on every facet of expenses deemed significant. Vehicle scheduling and vehicle route planning are options for solving cost problems. The optimized parameters involved the hourly residual battery capacity and battery charging times during the daytime operating hours. The results showed that although daytime charging involved electricity uses during peak hours and thus incurred additional costs, it contributed to the use of e-buses and an overall reduction in construction costs.

    In summary, the proposed optimization method would successfully reduce the construction cost of the Penghu e-bus transportation system (Ke et al., 2016).  The studies mentioned above were conducted when buses were already available. The results of these studies are needed to complete the bus design to be made.

       In this study, a bus will be planned according to the route taken, namely the inner city of Jakarta. The data or conclusions from this research are expected to be the basis for making an appropriate electric bus. In general, on electric buses, the powers for power steering and compressed air are generated from a separate electric motor. These powers are obtained from the crankshaft rotation on buses with diesel engines. Research to electrify bus brakes is also carried out to simplify control and reduce losses (Budiono et al., 2020; Nugraha et al., 2021; Nazaruddin et al., 2020). The type and number of transmission acceleration levels are also necessary because, without a gearbox, the power and torque losses will be very significant (Rahman et al., 2022). Meanwhile, small electric car planning with the help of GPS and software is carried out to minimize trial and error in determining the main motor and the number of batteries (Sumarsono et al., 2021).

     The challenge of this research are:

·      The low population of electric buses in Jakarta or Indonesia. So, data collection requires a unique strategy;

·      the absence of regulations regarding electric buses makes the problem boundaries must be processed so that they are not too broad;

·      the procurement of buses must be based on planning according to the needs and conditions in the field.

   With this fact, this research offers a solution for designing motor and battery power needs with a combination strategy of theoretical examination and simulation with GPS data and mechanical properties. The target is to develop a bus that fits the needs of the route with a little trial and error. It also proves the usefulness and importance of the RCAVe-EV1 software designed by the University of Indonesia.

Conclusion

Strava GPS data, RCAVe-EV1 software, and additional data from the interviews were beneficial and provided data and conclusions about the required electric bus specifications. Motor and battery power capacity is adjusted to the needs and bus routes. The power and torque can be minor for the inner bus with a relatively low speed. Besides, the battery capacity does not need to be too large with the correct charging strategy. It is so that the space for passengers remains wide. The use of design software and route data taken with GPS greatly helps the accuracy of the design. Bus operating costs are relatively competitive compared to conventional buses. In addition, even though the study results have not included an incentive factor from the government. The service life of electric buses can be longer than ten years because the motor's efficiency is relatively more stable than an internal combustion engine. For Transjakarta bus with the route of Blok M – Raden Inten, it can be considered that the bus transmission in the city can be simplified. It is also advantageous in terms of vehicle weight and maintenance costs. The 100 kW rated electric motor (200 kW max.) can provide a maximum torque of about 700 Nm. Then, with a bus operating time of 19 hours per day, there is a stop time of 5 hours. This time can be used for maintenance and charging the battery. Thus, the ideal time for charging is around 4 hours or less than 5 hours.

Acknowledgement

This research was supported by Lembaga Pengelola Dana Pendidikan –the Ministry of Finance Republic of Indonesia, with the contract number PRJ-86/LPDP/2020.

References

Adheesh. S.R.. . Vasisht. M.S.. Ramasesha. S.K.. 2016. Air-Pollution and Economics: Diesel Bus Versus Electric Bus. Current Science. Volume 110(5). pp. 858862

Al-Ogaili. A.S.. Ramasamy. A.. Hashim. T.J.T.. Al-Masri. A.N.. Hoon. Y.. Jebur. M.N.. Verayia. R.. Marsadek. M.. 2020. Estimation of the Energy Consumption of Battery Driven Electric Buses by Integrating Digital Elevation and Longitudinal Dynamic Models: Malaysia as a Case Study. Applied Energy. Volume 280. p. 115873

An. K.. 2020. Battery Electric Bus Infrastructure Planning under Demand Uncertainty. Transportation Research Part C: Emerging Technologies. Volume 111. pp. 572587

Bi. Z.. Song. L.. De Kleine. R.. Mi. C.C.. Keoleian. G.A.. 2015. Plug-In vs Wireless Charging: Life Cycle Energy and Greenhouse Gas Emissions for an Electric Bus System. Applied Energy. Volume 146. pp. 1119

Budiono. H.D.. Sumarsono. D.A.. Adhitya. M.. Baskoro. A.S.. Saragih. A.S.. Prasetya. S.. Zainuri. F.. Nazaruddin. Heryana. G.. Siregar. R.. 2020. Development of Smart Magnetic Braking Actuator Control for a Heavy Electric Vehicle. International Journal of Technology. Volume 11(7). pp. 13371347

Chen. Z.. Yin. Y.. Song. Z.. 2018. A Cost-Competitiveness Analysis of Charging Infrastructure for Electric Bus Operations. Transportation Research Part C: Emerging Technologies. Volume 93. pp. 351366

Ding. H.. Hu. Z.. Song. Y.. 2015. Value of the Energy Storage System in an Electric Bus Fast Charging Station. Applied Energy. 157. 630639

Jun-Qiang. X.. Guang-Ming. X.. Yan. Z.. 2008. Application of Automatic Manual Transmission Technology in Pure Electric Bus. In: IEEE Vehicle Power and Propulsion Conference (VPPC). September 3-5. 2008. Harbin. China

Ke. B.-R.. Chung. C-Y.. Chen. Y.-C.. 2016. Minimizing the Costs of Constructing an All Plug-In Electric Bus Transportation System: A Case Study in Penghu. Applied Energy. Volume 177. pp. 649660

Nazaruddin. Adhitya. M.. Sumarsono. D.A.. Siregar. R.. Heryana. G.. 2020. Review of Electric Power Steering Type Column Steering with Booster Motor and Future Research for EV-Bus. In: AIP Conference Proceedings. p. 020016. AIP Publishing LLC

Nugraha. A.A.. Sumarsono. D.A.Adhitya. M.. Prasetya. S.. 2021. Development of Brake Booster Design for Electric City Cars. International Journal of Technology. Volume 12(4). pp. 802-812

Pelletier. S.. Jabali. O.. Mendoza. J.E.. Laporte. G.. 2019. The Electric Bus Fleet Transition Problem. Transportation Research Part C: Emerging Technologies. Volume 109. pp. 174193

Peng. J.. He. H.. Xiong. R.. 2017. Rule Based Energy Management Strategy for a Series–Parallel Plug-In Hybrid Electric Bus Optimized by Dynamic Programming. Applied Energy. Volume 185. pp. 16331643

Rahman. A.. Hassan. N.. Ihsan. S.I.. 2022. Fuzzy Logic Controlled Two Speed Electromagnetic Gearbox for Electric Vehicle . International Journal of Technology. Volume 13(2). pp. 297309

Sumarsono. D.A.. Heryana. G.. Adhitya. M.. Siregar. R.. 2021. Performance Analysis of a Main Drive Motor—Initial Study of an EV Modeling Software Design. World Electric Vehicle Journal. Volume 12(4). p. 114

Teoh. L.E.. Khoo. H.L.. Goh. S.Y.. Chong. L.M.. 2018. Scenario-Based Electric Bus Operation: A Case Study of Putrajaya. Malaysia. International Journal of Transportation Science and Technology. Volume 7(1). pp. 1025

Xiong. W.. Zhang. Y.. Yin. C.. 2009. Optimal Energy Management for a Series–Parallel Hybrid Electric Bus. Energy Conversion and Management. Volume 50(7). pp. 17301738

Zhou. B.. Wu. Y.. Zhou. B.. Wang. R.. Ke. W.. Zhang. S.. Hao. J.. 2016. Real-World Performance of Battery Electric Buses and Their Life-Cycle Benefits with Respect to Energy Consumption and Carbon Dioxide Emissions. Energy. Volume 96. pp. 603613