Driving cycle is commonly known as the relationship between speed and time of a vehicle. Major application of driving cycle is to aid vehicle manufacturers, traffic engineers and environment engineers regarding pollution and emission studies. To develop an accurate driving cycle, information on realtime based driving behaviour is important. This paper concentrates on three major phases: to model a conceptual design of driving cycle tracking device (DC-TRAD) for route-to-work driving cycle in Kuala Terengganu city (RTW DC in KT city) in MATLAB/Simulink environment; to develop a prototype of DC-TRAD for RTW DC in KT city; and to analyse the obtained results of conceptual design and prototype for DC-TRAD using RTW DC in KT city. This research validates the conceptual model and prototype of DC-TRAD on RTW DC in KT city and the results obtained in this research supports the idea of importance of driving cycle.
<span>Driving cycle is commonly known as a series of speed-time profile. Research on this discipline aids vehicle manufacturing industries in vehicle manufacturing, environmentalists to study on environment quality and profile in accordance to vehicle emissions besides traffic engineers to further investigate the behavior of drivers and the conditions of roads in a certain area or cluster. This also assists automotive industries to innovate energy efficient vehicles which reduce vehicle emissions and energy wastages which lead to air pollution in which a major threat for human health according to Goal 3 of united nations (UN) sustainable development goals (SDG). To construct an accurate driving cycle, data based on real-world driving behavior is crucial and as the world is advancing in technology, the usage of internet of things (IoT) plays an important role in innovatietcons. IoT is an idea of computing every day physical object and information into computers, devices and software. These devices work by using sensors that transmit data to a computer or software allowing them to perform important tasks as needed. In this research, an idea of data collecting device, driving cycle tracking device (DC-TRAD) is constructed with implementation of IoT in which the collected data will be saved into my structured query language (MySQL) database instantly for data storing.</span>
Over the years, many models have been created to estimate pollution inventories and fuel usage. These models can be divided into two types: travel-based and fuel-based. One of the most used travel-based models for estimating emission inventories is driving cycles. It can be used for a variety of different things, such as establishing pollution regulations, traffic control, and calculating journey time. For these goals, researchers have previously attempted to use easily available, well-established driving cycles. In many ways, however, the local environment differs greatly from that of the driving cycle's genesis. As a result, these cycles' applications have failed to provide high-quality results. This research aims to analyse the various approaches utilised for driving cycle construction in various locations of Malaysia under varied operational situations.
Driving cycle is a series of speed versus time profile used to represent driving patterns of a vehicle. research in this field guides vehicle manufacturers and environmentalists to investigate air quality through emissions. Study on driving cycle also aids manufacturers to manage vehicle emissions and to save energy released through exhaust. Also, driving cycles can provide information on road condition and driving behaviour of an individual. For that, a proper data collection method is crucial as it is solely based on real world driving. This research is an initiative to construct a prototype of driving cycle tracking device (DC-TRAD) in which it was implemented with internet-of-things (IoT) to manage big number of collected data. U-Blox global positioning system (GPS) neo 7 M sensor was used to increase the accuracy of data capturing and it was used on route-to-work for Kuala Terengganu city (RTW DC for KT city) for analysis.
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