Browsing by Author "Gajanayake, S"
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- item: Conference-Full-textAnalyzing the battery thermal behaviour under Sri Lankan driving and ambient conditions(IEEE, 2023-12-09) Padmaperuma, C; Dissanayake, P; Gajanayake, S; Abeysooriya, R; Adikariwattage, V; Hemachandra, KOn par with the technological advancements, the usage of electric vehicles (EVs) has been significantly prevalent in most parts of the world, even in the developing third world countries. During the study, it focusses on the battery electric vehicles (BEVs) and an analysis on the thermal behavior of the battery of a BEV is performed. A two-way analysis is conducted since both theoretical approach and the simulation-based approach are utilized. The thermal profile of the battery of a BEV is analyzed against the modelled localized driving pattern, i.e., Colombo Metropolitan Driving Cycle and when the analysis is performed, local ambient temperature conditions have been used. Functional relationships have been developed between the tractive power and the power generated from the battery and the thermal profile which is determined theoretically is compared against the simulation-based battery thermal profile which is generated using MATLAB Simscape development environment. Significant similarities are witnessed between the theoretical plots and the plots which are generated by the simulations whereas certain discrepancies have also been identified and critically analyzed.
- item: Conference-AbstractA data acquisition methodology for the development of local driving cycles(Department of Civil Engineering, University of Moratuwa, 2020-12) Gajanayake, S; Bandara, S; Sugathapala, T; Perera, HLKDriving Cycles (DCs), the time speed profiles of a certain vehicle type for a given road segment can be considered as one of the main tools to quantify and to assess the performance in terms of fuel economy and emissions of a given vehicle category. There have been numerous approaches that have been adopted to develop DCs locally, representing various geographical regions of the world. Despite various approaches adopted, the researchers have defined a four-stepped common methodology for DC development viz. Route Selection, Data Acquisition, Cycle Construction and Cycle Assessment. During the study, approaches have opted under each step pertaining to the purpose of the DC development, i.e. for the characterization of fuel economy. Acquisition of data for DC development is one of the most important steps of the procedure since the representativeness of the DC of local driving behaviour depends on the quality of the data collected. Regardless of the approach adopted, the acquired data should be reliable, representative, consistent and homogeneous. The three main approaches that are in practice throughout the world can be listed viz. chase-car method, instrumented-car method and hybrid method. During this study, more focus is concentrated on suggesting a methodology of data collection for DC development. Since local driving behaviour incorporates irregular kinematic patterns integrated with aggressive driving behaviour, the instrumented-car method has opted over the chase-car method. Moreover, the operational complexity and the cost associated with the latter approach is higher than that of the opted method. Furthermore, on par with the introduction of On-Board Diagnostics (OBD) protocol as a worldwide standard for automobiles in the later 1990s, the invention of many OBD data logging devices happened. Consequently, the data logging on an automobile has been made convenient than ever. When it’s funnelled down to the instrumented-car method, the techniques in practice can be listed under two main categories viz. device-based methods and device and app-based methods. In device-based methods, the data are saved in internal storage and then it’ll be transferred for analysis. On the other hand, the device and app-based method facilitate the real-time data to be transferred to the connected app-hosting device viz. a mobile device, tablet or a laptop. In the latter method, the data logging device is connected with the app-hosting device primarily via Bluetooth or WIFI. Car manufacturers have introduced their own OBD data logging devices with internal storage viz. Chrysler DRBIII, Ford New Generation Star Tester, General Motors Tech II, Toyota Diagnostic Tester, Nissan Consult, VAG 551, etc. The said devices have mostly been introduced with the manufacturers’ proprietary technology which has made them costlier. Due to the cost factor in the device-based method, most of the researchers have adopted device and app-based methods which have come up with low-cost alternatives. A dedicated data logging device, ELM-327 adapter has opted for the research study. Due to its lower cost and hence multiple devices can be used for parallel data collection in vehicles. Out of several third-party software applications for OBD data logging, Torque ProTM has been opted for the study mainly due to its feature-rich interface, operational convenience and compatibility with a wider range of vehicle variants. The data is sampled at a frequency of 1 Hz. The logged data onto the app-hosting device is saved in two main types i.e. ‘.csv’ file type and ‘.kml’ file type. The mechanical parameters viz. engine speed and fuel flow rate, the spatial parameters viz. latitude, longitude and altitude have been logged using the said device-app arrangement. During the study, data is planned to collect from two-wheelers (2W), three-wheelers (3W) and four-wheelers (4W). The initial phase of the study would be to analyze the data streams pertaining to 2W, 3W and 4W, then evaluate whether there are significant discrepancies among the driving behaviours and patterns. Then the second phase of data collection would be conducted to develop the local driving cycle. Unlikely in 4W, in 2W and 3W, an OBD port cannot be found in common. Thus, an app-based data acquisition method is recommended for 2W and 3W. With respect to this case, several readily available applications are tested. The major limitations of the applications are that they log data at lower frequencies such as less than 1 Hz and the operational difficulty of obtaining the logged data from the users’ devices since the real-time data logging feature is unavailable in most. Therefore, a locally developed application at the University of Moratuwa which suits the data collection requirements has opted. The sample size has been selected as thirty vehicles from each category, accounting for ninety vehicles altogether in all three types. The geography of data collection has been selected as the urban areas of Colombo City.
- item: Conference-Full-textStudy of the impact of electric vehicles on fuel consumption and carbon dioxide emission scenarios in Sri Lanka(IEEE, 2020-07) Gajanayake, S; Thilakshan, T; Sugathapala, T; Bandara, S; Weeraddana, C; Edussooriya, CUS; Abeysooriya, RPOn par with the rapid motorization, fuel consumption and emission of greenhouse gases (GHGs) have become major challenges in the contemporary automotive industry. With a registered vehicle fleet of around 7.7 million road-vehicles and with an average survival rate of approximately 70%, Sri Lanka claims to an active vehicle fleet of around five million as of 2017. It can conspicuously be cited that 92% of the entire active fleet consists of Light Duty Vehicles which can be defined as the road-vehicles with a Gross Vehicle Weight Rating less than 3.5 tons. United Nations’ (UN) Sustainable Development Goals (SDGs) state ‘Affordable and clean energy as its 7th goal under which the target 7.3 is ‘doubling the improvement in energy efficiency’ directly aligns with the aim of the research study. Out of several approaches to mitigate the impacts of fuel consumption and emissions, electrification of the existing fleet and opting for electric vehicles as a new potential vehicle can be opted. The study analyses on the impact of electric two-wheelers, three-wheelers and cars on the fuel consumption and emission of GHGs in the national context forecasting on the future trends with increase in electric dominance to the traditional internal combustion engine vehicle.