Characterisation and development of driving cycle for work route in Kuala Terengganu


  • I. N. Anida
  • I. S. Ismail
  • J. S. Norbakyah
  • W. H. Atiq
  • A. R. Salisa



Driving cycle; micro-trip; optimisation; genetic algorithms, UDDS, EPA, HWFET


Driving cycle is essential for researchers and also vehicle developers to study the performance of the vehicle mainly via simulations. However, the driving cycles are not the same for different countries or cities, although they may seem identical. In this paper, several driving cycle data were collected for different routes in Kuala Terengganu city at peak hours which were then split into several micro-trips. A genetic algorithm was used as a procedure for selecting the optimised micro-trip to develop a complete Kuala Terengganu driving cycle. Then, the proposed driving cycle was compared with other existing driving cycles such as Urban Dynamometer Driving Schedule, Highway Fuel Economy Test Cycle, Supplemental Federal Test Procedure and Environmental Protection Agency. The proposed complete Kuala Terengganu driving cycle was successfully developed with 10 micro-trips and a total time of 1600s. The results showed that the comparison of percentages error for characteristic parameters for the KT and UDDS driving cycle was the lowest at 161.4 percent compared to others. This indicated that KT driving cycle and UDDS driving cycle is similar to each other as the driving cycle for cities. As a conclusion, the KT driving cycle was successfully obtained using the GA method with all of the percentage error for all parameters of below 10 percent, except for the percentage of cruise time. The results for the comparison also proved that the KT driving cycle is similar to UDDS driving cycle where both are the driving cycle for cities.




How to Cite

I. N. . Anida, I. S. Ismail, J. S. . Norbakyah, W. H. . Atiq, and A. R. . Salisa, “Characterisation and development of driving cycle for work route in Kuala Terengganu”, Int. J. Automot. Mech. Eng., vol. 14, no. 3, pp. 4508–4517, Dec. 2022.