Driving cycle for small and medium duty engine case study of Ipoh

Driving cycles is a series of data points representing the speed of vehicle verses time sequenced profile developed for certain road, route, specific area or city. It is widely used of application for vehicle manufacturers, environmentalists and traffic engineers. The purposes of this study are; to analyse the real world driving pattern and to develop a driving cycle for small and medium duty engines in Ipoh, Malaysia. This study carried out a survey to describe the motorcycle and car driving cycle on the selected three routes in the peak hour periods of the traffic condition, which are morning, afternoon and evening peak periods. The study used a GPS equipment to record vehicle travel speeds (second by second). The driving characteristics were analysed from speed time data and its target statistic parameters were defined. The method for generating the driving cycle has been described. The analysis results show that there are significant difference of driving characteristic and driving cycle between motorcycle and car for Ipoh city. The characteristic of the developed driving cycle for car was compared with three well established worldwide driving cycles. This information gives a clear message that those driving cycle such as ECE driving cycle (for instance) is not suitable to predict the emission standard in Ipoh. The driving cycle for motorcycle also had been compared with existing motorcycles driving cycles for Malaysia. It shows that the average speed of the developed Ipoh motorcycles driving cycle is higher than motorcycles driving cycle for Malaysia. The result clearly shows the driving cycle is dependent on specific area or city due to the different of traffic flow

Hydrogen-fueled postal vehicle performance evaluation

Fuel consumption, range, and emissions data were obtained while operating a hydrogen-fueled postal delivery vehicle over a defined Postal Service Driving Cycle and the 1975 Urban Driving Cycle. The vehicle's fuel consumption was 0.366 pounds of hydrogen per mile over the postal driving cycle and 0.22 pounds of hydrogen per mile over the urban driving cycle. These data correspond to 6.2 and 10.6 mpg equivalent gasoline mileage for the two driving cycles, respectively. The vehicle's range was 24.2 miles while being operated on the postal driving cycle. Vehicle emissions were measured over the urban driving cycle. HC and CO emissions were quite low, as would be expected. The oxides of nitrogen were found to be 4.86 gm/mi, a value which is well above the current Federal and California standards. Vehicle limitations discussed include excessive engine flashbacks, inadequate acceleration capability the engine air/fuel ratio, the water injection systems, and the cab temperature. Other concerns are safety considerations, iron-titanium hydride observed in the fuel system, evidence of water in the engine rocker cover, and the vehicle maintenance required during the evaluation

Analisa Gaya, Porsi, Kontribusi Dan Efisiensi Sistem Rem Regeneratif pada EZZY ITS II

Driving cycle merupakan serangkaian data yang mewakili kecepatan kendaraan versus waktu sebagai bentuk representasi dari keadaan jalan tertentu yang sebenarnya. Kepentingan dari penggunaan Driving cycle dalam menganalisa kendaraan adalah mengurangi biaya tes jalan, waktu tes dan kelelahan pengemudi. Driving cycle yang digunakan pada penelitian sebelumnya mengenai bus Transjakarta kurang mempresentasikan keadaan jalan dalam kota yang sebenarnya karena banyaknya kecepatan konstan yang terjadi. Sehingga hasil analisanya kurang akurat apabila diaplikasikan secara langsung. Penelitian ini dilakukan untuk menganalisa lebih dalam mengenai sistem rem regeneratif pada mobil listrik. Jenis kendaraan yang diteliti adalah city car EZZY ITS II sebagai objek penelitian dan menganalisa sistem rem regeneratifnya dengan Driving cycle Prius dan WLTP. Pemakaian city car adalah karena jenis kendaraan ini banyak digunakan oleh masyarakat. Penambahan Driving cycle Prius adalah untuk mendapatkan hasil yang lebih akurat dengan kondisi jalan di Surabaya. Penelitian dimulai dengan analisa porsi dan gaya pengereman mekanis dan regeneratif kendaraan. Tujuannya adalah agar kendaraan tetap stabil saat pengereman. Penelitian dilanjutkan dengan analisa kontribusi dan efisiensi sistem rem regeneratif pada tiap Driving cycle. Analisa ini bertujuan untuk mengetahui besarnya pengaruh sistem rem regeneratif pada mobil listrik dan membandingkan hasil analisanya berdasarkan Driving cycle yang digunakan. Hasil dari penelitian ini didapati sistem rem regeneratif pada kendaraan bekerja secara penuh pada rentang j/g 0-0,8 untuk gear pertama. Hasil penelitian ini cukup signifikan dikarenakan rem regeneratif dapat menggantikan peran rem mekanis roda depan kendaraan. Kontribusi sistem rem regeneratif yang didapatkan adalah 38,82% untuk Driving cycle Prius dan 30,36% untuk Driving cycle WLTP. Efisiensi sistem rem regeneratif yang didapatkan 67,94% untuk Driving cycle Prius dan 58,94% untuk Driving cycle WLTP. Kontribusi dan efisiensi yang didapatkan tersebut sudah lebih baik daripada penelitian sebelumnya

Development of a vehicle robotic driver with intelligent control system modelling for automated standard driving-cycle tests

New road vehicles are required to undergo several specific tests to meet the requirement set by governing bodies in various markets. These tests are often carried out over specific driving-cycles. To carry out lab-based driving-cycle tests, a typical vehicle manufacturer will employ a trained driver to follow driving profiles on a chassis dynamometer. This project involves development of a robotic driver controller for the automation of dynamometer-based vehicle testing according to industry standard driving cycle tests and produce repeatable results by replacing the traditional method of employing a human driver with a robot driver. The throttle and brake pedals control systems modelling and design for automatic transmission vehicle are implemented, with Fuzzy model reference adaptive control (Fuzzy MRAC) as the main controller. The vehicle model was developed using black-box modelling approach where simulations are performed based on real-time data and processed using Matlab System Identification tool. The Fuzzy MRAC was then designed within the simulations to attain the driving performance. The vehicle model response was sent as feedback to the robotic DC linear actuator motor which was modelled based on DC linear actuator motor design specification. The results obtained from simulation and modelling experiment were discussed and compared. The performed work concludes that system identification modelling with best fit accuracy of 79.93% can be applied in Fuzzy MRAC to ensure smooth and accurate vehicle driving pattern behavior even when the leading vehicle exhibits highly dynamic speed behavior during driving-cycle test. The performance of the vehicle model has shown an average 0.07 MSE for the throttle system and 0.008 MSE for the brake system of the vehicle model

Driving Cycle Analysis for Fuel Economy and Emissions in Kuala Terengganu during Peak Time

Number of vehicles grows rapidly in Kuala Terengganu by year. This increment is troubled by the performance of the vehicle regarding pollutants generated. Plug-in hybrid electric vehicles (PHEV) are widely considered to be the most promising vehicles instead of the traditional engine vehicles to reduce fuel consumption and exhaust gas emission. The objectives of this paper are to develop driving cycle of Kuala Terengganu and to analyse the fuel economy and emissions in Kuala Terengganu during peak time. Driving cycle is where PHEV is used as the main apparatus to determine the driving cycle data. In this study, the on-road measurement method is used to collect the data, along with the global positioning system. This technique involves recording speedtime dataset in the real-world driving cycle. Three main methods to identify the best driving cycle are route selection, data collection and data analysis. The data were analysed to get the best driving cycle using a computer program, which is Mathematical Laboratory (MATLAB), along with validated parameters

Driving cycle development for Kuala Terengganu city using k-means method

Driving cycle plays a vital role in the production and evaluating the performance of the vehicle. Driving cycle is a representative speed-time profile of driving behavior of specific region or city. Many countries has developed their own driving cycle such as United State of America, United Kingdom, India, China, Ireland, Slovenia, Singapore, and many more. The objectives of this paper are to characterize and develop driving cycle of Kuala Terengganu city at 8.00 a.m. along five different routes using k-means method, to analyze fuel rate and emissions using the driving cycle developed and to compare the fuel rate and emissions with conventional engine vehicles, parallel plug-in hybrid electric vehicle, series plug-in hybrid electric vehicle and single split-mode plug-in hybrid electric vehicle. The methodology involves three major steps which are route selection, data collection using on-road measurement method and driving cycle development using k-means method. Matrix Laboratory software (MATLAB) has been used as the computer program platform in order to produce the best driving cycle and Vehicle System Simulation Tool Development (AUTONOMIE) software has been used to analyze fuel rate and gas emission. Based on the findings, it can be concluded that, Route C and single spilt-mode PHEV powertrain used and emit least amount of fuel and emissions

CHOOSING DRIVING CYCLE OF HYBRID VEHICLE

The analysis of existing driving cycles was performed. After comparing some of the cycles, one specific driving cycle was selected for the hybrid vehicle as the most reliable in representing the real moving of the vehicle in operating conditions and which may be reproduced at experimental tests at the modeling roller stand

Utilization of waste heat in trucks for increased fuel economy

The waste heat utilization concepts include preheating, regeneration, turbocharging, turbocompounding, and Rankine engine compounding. Predictions are based on fuel-air cycle analyses, computer simulation, and engine test data. All options are evaluated in terms of maximum theoretical improvements, but the Diesel and adiabatic Diesel are also compared on the basis of maximum expected improvement and expected improvement over a driving cycle. The study indicates that Diesels should be turbocharged and aftercooled to the maximum possible level. The results reveal that Diesel driving cycle performance can be increased by 20% through increased turbocharging, turbocompounding, and Rankine engine compounding. The Rankine engine compounding provides about three times as much improvement as turbocompounding but also costs about three times as much. Performance for either can be approximately doubled if applied to an adiabatic Diesel