Fuel saving index assessment on driving behavior control system of prototype model using neural network





Fuel Saving Index, fuel consumption, FSI, stoichiometry, driving behaviour, neural network


Efficient fuel consumption in the world is essential in automotive technology development due to the increase in vehicle usage and the decrease in global oil production. Several studies have been conducted to increase fuel consumption savings, Fuel Cells (FCs), the application of alternative energy vehicles and the Engine Control Unit (ECU) system. FCs do not require oil energy to propel the vehicle, so this technology promises to reduce energy consumption and emissions. However, this research still leaves problems. FCs are susceptible to short circuit hazards, and ownership costs are very high. Alternative energy applications produce less power, less responsive acceleration, and insufficient energy sources to enter mass production. The ECU application still has an orientation toward achieving stoichiometry values, so the increase in fuel efficiency has the potential to be improved. Driving behavior is a variable that has a close relationship with fuel consumption efficiency. However, research on driving behavior is only studied for implementation in autonomous car-following technologies, safety systems, charging needs characteristic of electric vehicles, emission controls, and display images on invehicle information systems. Meanwhile, research on driving behavior as a control system to improve fuel efficiency has not been carried out. To that end, this study proposes the use of driving behavior for a newly designed control system to improve fuel efficiency. The control system in this research is a prototype model to be assessed using the Fuel Saving Index (FSI) analysis. An artificial neural network is used to help the recognition of driving behavior. The results showed that the newly designed control system was categorized on scale IV of FSI. On this scale, the power generated by the engine is quite optimal when it is in the eco-scheme driving behavior. The driving behavior control system can significantly improve the efficiency of fuel consumption. Air to Fuel Ratio (AFR) is achieved above the stoichiometric value.


Ahmed, S., & Al, F. (2019). Analyzing and predicting the relation between air – fuel ratio (AFR), lambda ( λ ) and the exhaust emissions percentages and values of gasoline fueled vehicles using versatile and portable emissions measurement system tool. SN Applied Sciences, 1(11), 1-12. DOI: 10.1007-s42452-019-1392-1395.

Al-fattah, S. M. (2020). Non-OPEC conventional oil : Production decline, supply outlook and key implications. Journal of Petroleum Science and Engineering, 189, 107049. DOI: 10.1016/j.petrol.-2020.107049.

Alper, A., & Do, Y. (2018). Investigation of the effects of gasoline and CNG fuels on a dual sequential ignition engine at low and high load conditions. Fuel, 232(May), 114-123. DOI: 10.1016/j.fuel.-2018.05.156.

Ashkrof, P., Homem, G., Correia, D. A., & Arem, B. Van. (2020). Analysis of the effect of charging needs on battery electric vehicle drivers ’ route choice behaviour : A case study in the Netherlands. Transportation Research Part D, 78, 102206. DOI: 10.1016/j.trd.2019.102206.

Biswal, A., Gedam, S., Balusamy, S., & Kolhe, P. (2020). Effects of using ternary gasoline-ethanol-LPO blend on PFI engine performance and emissions. Fuel, 281(July), 118664. DOI: 10.1016/j.fuel.-2020.118664.

Fadhloun, K., & Rakha, H. (2020). A novel vehicle dynamics and human behavior car-following model : Model development and preliminary testing. International Journal of Transportation Science and Technology, 9, 14-28. DOI: 10.1016/j.ijtst.2019.05.004.

Grove, K., Soccolich, S., Engström, J., & Hanowski, R. (2019). Driver visual behavior while using adaptive cruise control on commercial motor vehicles q. Transportation Research Part F: Psychology and Behaviour, 60, 343-352. DOI: 10.1016/j.trf.2018.10.013.

Hong, Z., Chen, Y., & Wu, Y. (2020). A driver behavior assessment and recommendation system for connected vehicles to produce safer driving environments through a “follow the leader” approach. Accident Analysis and Prevention, 139(November 2019), 105460. DOI: 10.1016/j.aap.2020.105460.

Kohl, J., Gross, A., Henning, M., & Baumgarten, T. (2020). Driver glance behavior towards displayed images on in-vehicle information systems under real driving conditions. Transportation Research Part F: Psychology and Behaviour, 70, 163-174. DOI: 10.1016/j.trf.2020.01.017.

Martinelli, F., Mercaldo, F., Orlando, A., Nardone, V., Santone, A., & Kumar, A. (2020). Human behavior characterization for driving style recognition in vehicle system R. Computers and Electrical Engineering, 83, 102504. DOI: 10.1016/j.compeleceng.2017.12.050.

Martyr, A.., & Plint, M. (2007). Engine Testing Theory and Practice. Elsevier Ltd. Retrieved from https://id1lib.org/book/563256/1abf18.

Mehra, R. K., Duan, H., Luo, S., Rao, A., & Ma, F. (2018). Experimental and artificial neural network ( ANN ) study of hydrogen enriched compressed natural gas ( HCNG ) engine under various ignition timings and excess air ratios. Applied Energy, 228(April), 736-754. DOI: 10.1016/j.apenergy.-2018.06.085.

Monika, A. Z., Chlopek, Z., Merkisz, J., & Pielecha, J. (2022). Analysis of The Operation State of Internal Combustion Engine in The Real Driving Emissions Test. Archives of Transport, 61(1), 71-88. DOI: 10.5604/01.3001.0015.8162.

Munahar, S., Condro, B., Muji, P., Aris, S., Joga, T., & Setiawan, D. (2020). Design and application of air to fuel ratio controller for LPG fueled vehicles at typical down way. Springer Nature, (August 2019), https://doi.org/10.1007/s42452-019-1839-8. DOI: 10.1007/s42452-019-1839-8.

Nguyen, K., & Nguyen, V. (2018). Energy for Sustainable Development Study on performance enhancement and emission reduction of used fuel-injected motorcycles using bi-fuel gasoline-LPG. Energy for Sustainable Development, 43, 60-67. DOI: 10.1016/j.esd.2017.12.005.

Reinolsmann, N., Alhajyaseen, W., Brijs, T., Pirdavani, A., Hussain, Q., & Brijs, K. (2019). Investigating the impact of dynamic merge control strategies on driving behavior on rural and urban expressways – A driving simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 65, 469-484. DOI: 10.1016/j.trf.2019.08.010.

Robertson, D., & Prucka, R. (2020). Evaluation of autoignition models for production control of a spark-assisted compression ignition engine. International Journal of Engine Research, 1-13. DOI: 10.1177-/1468087420934555.

Sardarmehni, T., Aghili Ashtiani, A., & Menhaj, M. B. (2019). Fuzzy model predictive control of normalized air-to-fuel ratio in internal combustion engines. Soft Computing, 23(15), 6169-6182. DOI: 10.1007/s00500-018-3270-2.

Setiyo M. & Munahar, S. (2017). AFR and fuel cut-off modeling of LPG-fueled engine based on engine , transmission , and brake system using fuzzy logic controller (FLC). Journal of Mechatronics, Electrical Power, and Vehicular Technology, 8, 50-59. DOI: 10.14203/j.mev.2017.v8.50-59.

Sharma, A., Zheng, Z., Bhaskar, A., & Haque, M. (2019). Modelling car-following behaviour of connected vehicles with a focus on driver compliance. Transportation Research Part B, 126, 256-279. DOI: 10.1016/j.trb.2019.06.008.

Stogios, C., Kasraian, D., Roorda, M. J., & Hatzopoulou, M. (2019). Simulating impacts of automated driving behavior and traffic conditions on vehicle emissions. Transportation Research Part D, 76, 176-192. DOI: 10.1016/j.trd.2019.09.020.

Sun, B., Zhang, T., GE, W., Tan, C., & Gao, S. (2019). Driving Energy Management of Front - AND - Rear - Motor - Drive Electric Vehicle Based on Hybrid Radial Basis Function. Archives of Transport, 49(1), 47-58. DOI: 10.5604/01.3001.0013.2775.

Uslu, S., & Celik, M. B. (2020). Performance and Exhaust Emission Prediction of a SI Engine Fueled with I amyl Alcohol-Gasoline Blends : An ANN Coupled RSM Based Optimization. Fuel, 265, 116922. DOI: 10.1016/j.fuel.2019.116922

Vaezipour, A., Rakotonirainy, A., & Haworth, N. (2018). A simulator evaluation of in-vehicle human machine interfaces for eco-safe driving. Transportation Research Part A, 118, 696-713. DOI: 10.1016/j.tra.2018.10.022.

Wang, P., Gao, S., Cheng, L., & Zhao, H. (2020). Research On Driving Behavior Decision Making System Of Autonomous Driving Vehicle Based On Benefit Evaluation Model. Archives of Transport, 53(1), 21-36. DOI: 10.5604/01.3001.0014.1740.

Wang, Y., Shi, Y., Cai, M., & Xu, W. (2020). Predictive control of air-fuel ratio in aircraft engine on fuel-powered unmanned aerial vehicle using fuzzy-RBF neural network. Journal of the Franklin Institute, 357, 8342-8363. DOI: 10.1016/j.jfranklin.2020.03.016.

Wu, H., & Tafreshi, R. (2019). Observer-based internal model air-fuel ratio control of lean-burn SI engines. IFAC Journal of Systems and Control, 9, 100065. DOI: 10.1016/j.ifacsc.2019.100065.

Xing, Y., Lv, C., Cao, D., & Lu, C. (2020). Energy oriented driving behavior analysis and personalized prediction of vehicle states with joint time series modeling. Applied Energy, 261, 114471. DOI: 10.1016/j.apenergy.2019.114471.

Xiong, H., Liu, H., Zhang, R., & Yu, L. (2019). An energy matching method for battery electric vehicle and hydrogen fuel cell vehicle based on source energy consumption rate. International Journal of Hydrogen Energy, 44(56), 29733-29742. DOI: 10.1016/j.ijhydene.2019.02.169.

Yuan, Y., Lu, Y., & Wang, Q. (2020). Adaptive forward vehicle collision warning based on driving behavior. Neurocomputing, 408, 64-71. DOI: 10.1016/j.neucom.2019.11.024.

Zhao, X., Wang, Z., Xu, Z., Wang, Y., Li, X., & Qu, X. (2020). Field experiments on longitudinal characteristics of human driver behavior following an autonomous vehicle. Transportation Research Part C, 114, 205-224. DOI : 10.1016/j.trc.2020.02.018.






Original articles

How to Cite

Munahar, S., Triwiyatno, A., Munadi, M., & Setiavan, J. D. (2022). Fuel saving index assessment on driving behavior control system of prototype model using neural network. Archives of Transport, 63(3), 123-141. https://doi.org/10.5604/01.3001.0016.0019


Most read articles by the same author(s)

1 2 3 4 5 6 7 8 9 10 > >> 

Similar Articles

1-10 of 198

You may also start an advanced similarity search for this article.