Developing local driving cycle for accurate vehicular CO2 monitoring: A case study of Tehran. (15th February 2022)

• Record Type: Journal Article
• Authors: Mafi, Shahab; Kakaee, Amirhasan; Mashadi, Behrooz; Moosavian, Ashkan; Abdolmaleki, Saied; Rezaei, Mahdi
• Is Part Of: Journal of cleaner production. Volume 336(2022)
• Publication Date: 2022-02-15
• Subjects: Driving cycle -- Carbon footprint -- Sustainable transport -- Tehran -- K-means clustering -- Emission regulation; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2021.130176
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Driving cycles used in legislation are fixed schedules of vehicle operation for standard emission evaluation of different vehicles. Recently, the growing deviation of CO2 values obtained with standard driving cycles from those recorded in real driving has prompted the development of new driving cycles to better estimate CO2 emission. International Council of Clean Transportation (ICCT) reports about a 40% deviation when vehicles are tested under New European Driving Cycle (NEDC). The introduction of Worldwide harmonized Light vehicles Test Cycles (WLTC) has reduced the gap between lab and road to 20%. However, this gap is predicted to grow until more robust tests based on real driving emissions (RDE) are presented for 2025 and beyond. This growing gap is a significant concern for reducing the carbon footprint in the transport section. The present article discusses developing local driving cycles for reducing this gap in passenger vehicles. Two distinct cycles with a good approximation of real driving were developed using the k-means clustering method. The CO2 emission of a 5-door passenger vehicle in these cycles was estimated using computer simulation. Compared with NEDC and WLTC, 30% less deviation from average CO2 emission levels recorded in real driving profiles was obtained with generated local driving cycles. The benefits of local driving cycles in legislation and reaching interim targets in reducing carbon emissions were discussed. The authors suggested implementing local driving cycles in type approvals without robust procedures based on real driving emissions. Granting subsidies to vehicles complying with local type approvals is also suggested as a stimulating policy for car manufacturers to boost overseas markets. It is concluded that replacing legislative driving cycles used for emission estimation with local driving cycles can significantly improve carbon reduction before implementing RDE into legislation. Graphical abstract: Image 1 Highlights: Over 950 h of daily driving were recorded for five passenger vehicles in Tehran. The recorded driving data were pre-processed for duplicate and noise removal. Six driving states were assumed, and data distribution in these states was analyzed. Contrary to test cycles, the idle state is only 16% of driving time in Tehran. Two driving cycles were generated with a better approximation of real driving. CO2 emission of real and generated driving profiles was estimated by simulation. The CO2 gap between test and real driving in Tehran is estimated at 20–30%. The generated driving cycles reduced the CO2 gap to real-world to only 3–5%. Implementing local driving cycles in carbon reduction policies was suggested. It was concluded that local driving cycles could improve carbon monitoring.