Examining Of The Grade Rresistance S Effect On The Constituting Of The Driving Cycles

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2012Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2012Bu çalışmada seyir çevrimlerinin oluşturulmasında yokuş direnci etkisinin incelenmesi gerçekleştirilmiştir. Taşıtlardan kaynaklanan kirletici egzoz gazlarının belirlenmesine yönelik olarak gerçekleştirilen emisyon testlerinde taşıtlar laboratuar ortamında, şasi dinamometresi üzerinde Avrupa Test Çevrimi (NEDC), ABD Test Çevrimi (FTP) benzeri çevrimlere göre sürülerek test edilmektedir. Bu testler dolaylı olarak yokuş direncini içermekle birlikte, bu sürüş sırasında doğrudan taşıt yokuş direnci hesaplanamamaktadır. İstanbul Teknik Üniversitesi (İTÜ) Otomotiv Laboratuvarı’nda geliştirilen İstanbul Şehir Çevrimi’nde toplanan yol dataları değerlendirilerek, İstanbul şehrinde trafik akışını simüle etmek amacıyla bir çevrim oluşturulmuştur. Bu çevrimin oluşturulması için toplanan yol dataları istatistiksel olarak değerlendirilmiştir. Ancak bu çevrimde de yokuş direnci etkisi doğrudan dahil edilmemiştir. Bu çalışmada örnek parkur olarak Eski İstanbul Suriçi parkuru (Haliç Bölgesi, Sahil Yolu, Eminönü ve Sirkeci şeklindeki kapalı çevrim) kullanılmıştır. Veri toplama aracı ile farklı gün ve saatlerde kaydedilen GPS verileri kullanılmıştır. Bu veriler taşıtın konumunun zamana göre değişimini içermektedir. Bu verilerden faydalanarak taşıtın anlık hızı, ivmelenmesi, bulunduğu konum ve belirli zaman dilimi içerisinde yaptığı yol hesaplanmıştır. Ayrıca taşıt konumu 3-boyutlu kaydedildiği için taşıtın sürüş sırasındaki yokuş çıkış ve iniş değerleri de anlık olarak hesaplanmıştır. Taşıtın bulunduğu konum ve yükselti değerleri anlık olarak bilinmektedir. Zamana göre yükselti değerleri çeşitli eğri yumuşatma yöntemlerinden faydalanarak yumuşatılmıştır. Bu yöntemler; hareketli ortalama filtreleme, Savitzky-Golay, Lowess ve Loess olarak isimlendirilmektedir. Gerçek eğriye en yakın olan eğri seçilerek yeni yükselti değerlari elde edilmiştir. En yakın eğri belirlenirken eğrilerin altında kalan alanlar yamuk yönteminden faydalanarak hesaplanmıştır. Gerçek eğrinin altında kalan alana en yakın değeri olan eğri bu yeni yükselti değerlerini oluşturmaktadır. Yeni yükselti ve konum verileri ile anlık hız değerleri kullanılarak içerisinde aerodinamik, ivmelenme, yokuş ve yuvarlanma direnci değerlerini barındıran toplam direnç değerleri anlık olarak hesaplanmıştır. Yokuş direnicinin toplam dirence oranı bulunarak her bir an için yokuş direncinin toplam dirence olan etkisi belirlenmiştir. Sonraki aşamada yokuş direnci değerlerinin ivmelenmelerin içerisine eklenmesi için yeni bir yaklaşım geliştirilmiştir. Burada toplam direnç değerinin değişmemesine azami özen gösterilmiştir. Bu çalışma sonucu yokuş direncinin yakıt tüketimine ve egzoz emisyonlarına olan etkisidir. Burada üzerinde durulan önemli bir tanım taşıt özgül gücüdür. Taşıt özgül gücü; birim taşıt kütlesi başına motordan çekilen güç anlamına gelir. Bu ifade bünyesinde yol eğimini barındırmaktadır. Dolayısıyla yokuş direnci ile doğrudan ilişkilidir. Taşıt özgül gücü; yakıt tüketimi ve CO2, CO, HC, NOX, PM emisyon oranları artışı ile paralellik göstermektedir. Yani yol eğiminin dolayısıyla yokuş direncinin artışı beraberinde artan yakıt tüketimi ve yükselen egzoz emisyonları demektir. Bu sonuçlar akabinde sunlabilecek ileriye yönelik öneri ise hibrit araçların kullanımının artırılması, teşvik edilmesidir. Hibrit araçlar yokuş çıkarken normal içten yanmalı motorda olduğu gibi yeterli gücü sağlayamaz. Ancak ihtiyacı olan güç için fazladan yakıt kullanımı yerine elektrik motoru ve akü kullanarak yakıt tasarrufuna katkıda bulunur.Examinig of the grade resistance’s effect on the constituting of the driving cycles was put through in this study. Vehicle driving cycles have some areas of usage that are expressed as emission measurements of the vehicles, fuel consomption measurements, vehicle simulations. When emission tests of automobiles and the light commercial vehicles are realized with the chassis dynamometers, emission tests of heavy commercial vehicles and cross country vehicles are realized with the engine dynamometers. Emission measurements and fuel consumption measurements are not realized in this study. Vehicles are tested by driving on the basis of New European Driving Cycle (NEDC), USA Test Cycle (FTP) to be determined of the pollutant exhaust gases which were caused by vehicles in the laboratory environment on the chassis dynamometer. While this tests include the gradient resistance indirectly, vehicle’s gradient resistance can not calculate directly during the driving. A cycle was constituted with the purpose of simulating the traffic flow on Istanbul by being evaluated the road datas, which were collected on Istanbul City Cycle that was improved in Istanbul Technical University (ITU) Automotive Laboratory. Collected road datas were evaluated statistically by being constituted of this cycle. However, the effect of the grade resistance was not integrated directly in this cycle too. Istanbul City Cycle was prepared by being made use of a project that was named as Greenhouse Gas Emission on the Transportation Sector. Total four roads were determined that contain three main arterial roads and one the first and second degree arterial road that represent the flow characteristic of Istanbul City Traffic. When the main arterial roads, the first and the second arterial roads were selected, the classification, which was realized by Istanbul Metropolitan Municipality Directorate General of Transportation, was taken into account. BK (Bosphorus) Bridge Maslak-Göztepe, FSM (Fatih Sultan Mehmet) Bridge Maslak-Kozyatağı, E-5 Maslak-Bakırköy, Historical Peninsula (Coast Road, Vatan Caddesi, Edirnekapı) are the selected routes. The selected three routes come into existance the main arterial roads that are utilized on the cross town journeys and intercities journeys and that take place the huge amount on Istanbul Traffic Flow. Fourth route comes into existance the first and the second main arterial roads that represent the traffic flow in the towns. Old Istanbul Surici Track (closed loop that was occured by Golden Horn Region, Coast Road, Eminönü and Sirkeci) was used in this study as the sample track. GPS datas, which were recorded in the different days and hours with the data collection vehicle, were utilized. These datas include the change of vehicle’s position depending on time. Instant speed, acceleration, position and covering a distance for the specific period of time of the vehicle were computed by making use of these datas. Moreover, the values of upgrade and downgrade were calculated transiently during the driving since the position of vehicle was recorded three dimension. The location and height values of vehicle are known transiently. Height values, which depend on time, were smoothed by making use of various curve smoothing methods. These methods are named as Moving Average Filtering, Savitzky-Golay, Lowess and Loess. The data is smoothed by a moving average filter that is got involved in Moving Average Filtering by put each data point back with the average of the neighboring data points that are identified within the span. This process is equivalent to lowpass filtering with the response of the smoothing given by the difference equation. When the moving average filtering method is required, there are some rules. One of these rules is that the span must be odd. Another rule is that the data point to be smoothed must be at the center of the span. Another type of smoothing methods is Savitzky-Golay Filtering. Savitzky-Golay filtering can be thought as a generalized moving average. The filter coefficients are derived by performing an unweighted linear least squares fit using a polynomial of a given degree. For this reason, a Savitzky-Golay filter is also named a digital smoothing polynomial filter or a least squares smoothing filter. The Savitzky-Golay filtering method is often utilized with frequency data or with spectroscopic data. For frequency data, the method is effective on preserving the high frequency components of the signal. For spectroscopic data, the method is effective on preserving higher moments of the peak such as the line width. By comparison, the moving average filter tends to filter out a significant portion of the signal’s high frequency content, and it can only preserve the lower moments of a peak such as the centroid. “Lowess” and “Loess” are derived from the term “locally weighted scatter plot smooth”. Locally weighted linear regression is utilized to smooth data by both methods. The smoothing process is considered local because, each smoothed value is determined by neighboring data points defined within the span like the moving average method. The process is weighted because, a regression weight function is defined for the data points contained within the span. In addition to the regression weight function, which makes the process resistant to outliers. Finally, the methods are differentiated by the model utilized in the regression. New height values were obtained by being chosen the curve that is closest to the real one. While the closest curve was determined, the areas under the curves were calculated by making use of the trapezoid method. The curve, which has the closest value to the area under the curve constituted this new height values. Total resistance values, which contain aerodynamic, acceleration, gradient and rolling resistance values, were calculated transiently by being utilized the new height, position datas and instant speed values. The effect of gradient resistance to the total resistance was determined for every moment by being taken into account the ratio of the gradient resistance to the total resistance. Aerodynamic resistance depends on the aerodynamic drag coefficient, the air density, the frontal area of the vehicle, the speed of the vehicle and the speed of the wind. When the datas, which are used for the driving cycle, were collected, the wind speed was neglected because, any data was not carried out related to the wind speed during data collecting process. Inertia forces are influenced on the division that has accelerated motion during the driving of the vehicle. The genaral motion of the vehicle is accepted as an unaccelerated motion. However, the acceleration emerges during the first motion and breaking and, the inertia forces influence opposite direction of the acceleration. Inertia forces affect on the direction of the motion and the contributor to the motion during the breaking whereas, these inertia forces are not preferred and the breaking force is needed to overcome these inertia forces. Therefore, the forces, which come due to the acceleration, are generally mentioned as the inertia resistance. Gradient resistance emerges during the motion of the vehicle because of the component of the force of the gravity on the inclined road. Also, gradient resistance depends on the mass of the vehicle, gravitational acceleration and the slope angle of the road. Rolling resistance emerges from deformations of the road and tires and the hysteresis losses of the tires during the rolling of the wheels and, this resistance is expressed as a coefficient. This coefficient must be small as far as possible because, the wheel and the plastic deformation on the road determine the magnitude of the rolling resistance. For example, the deformation on the tire of the wheel that is rolled on the gumbo is named as elastic and the deformation on the gumbo is named as plastic. At this stage, air pressure is reduced to minimize the amount of the deformation on the gumbo. Therefore, the rolling resistance is cut into. However, the air pressure must be increased to reduce the rolling resistance of the vehicle that progresses on the asphalt road. At a later stage, a new approach was developed to be added the gradient resistance values inside the accelerations. Necessary was paid attention to not to change of total resistance values. Also, gradient resistance has a great effect on fuel consumption and exhaust emission. This effect is identified by vehicle specific power (VSP) that means to the power demand on the engine per unit vehicle mass. This parameter represents the tractive power exerted by a vehicle to move itself and its cargo or passengers. VSP was estimated based on typical coeeficient values that are expressed as rolling resistance coefficient and drag coefficient. Also, CO2, CO, HC, NOX, PM emission rates and fuel consumption emission rates have similar increasing trends as VSP increases. The usage of hybrid vehicles is one of the suggestions to provide the necessary energy storage. Battery in the hybrid vehicles is a unit that store the energy for the electric motor. Electric motor in the hybrid vehicles performs a duty as a genarator. When the vehicle accelerates, the motor provides the energy from battery. When the vehicle decelerates, the motor performs a duty as a genarator and, it stores the energy to the battery. Therefore, hybrid vehicles need a help to climb a grade because, the motor in the hybrid vehicles can only provide the power, which compensates a normal driving. So, this assistance is provided by the electric motor and the battery. Moreover, these systems, which are named as the electric motor and the battery, are utilized for the extreme power demand instead of the fuel. Hybrid vehicles are more advantageous than normal internal combustion engines for the great gradient resistance effect on the subject of fuel economy.Yüksek LisansM.Sc