No description available.

The aim of my diploma thesis was engineering design of 4x4 chassis dynamometer model at 1:10 scale for presentation purpose and for testing RC cars models. The first part describes the current types of chassis dynamometers. The main goal of the thesis was designed the model itself in order to produce some parts of the dynamometer using 3D printing. The work also includes production drawings of individual parts and economic estimate of the entire production.

No description available.

No description available.

In the European Union the legislation governing fleet CO2 emissions is already in place with a fleet average limit of 130g/km currently being imposed on all vehicle manufacturers. With the target for this legislation falling to 95g/km by 2020 and hefty fines for noncompliance automotive engineers are working a pace to develop new technologies that lower the CO2 emissions and hence fuel consumption of new to market vehicles. As average new vehicle CO2 emissions continue to decline the task of measuring these emissions with high precision becomes increasingly challenging. With the introduction of real world emissions legislation planned for 2017 there is a development driven need to precisely assess the vehicle CO2 emissions on chassis dynamometers over a wide operating range. Furthermore since all type approval and certification testing is completed on chassis dynamometers, any new technology must be proven against these test techniques. Typical technology improvements nowadays require repeatability limits which were unprecedented 5-10 years ago and the challenge now is how to deliver this level of precision. Detailed studies are conducted into the four key areas that cause significant noise to the CO2 emissions results from chassis dynamometer tests. These are the vehicle electrical system, driver behaviour, procedural factors and the chassis dynamometer itself. In each of these areas, the existing contribution of imprecision is quantified, methods are proposed then demonstrated for improving the precision and the improved case is quantified. It was found that the electrical system can be controlled by charging the vehicle battery, not using auxiliary devices and installing current measurement devices on the vehicle. Simply charging the vehicle battery prior to each test was found to cause a change to the CO2 emissions of 2.2% at 95% confidence. Whilst auxiliary devices were found to cause changes to the CO2 emissions of up to 43% for even a relatively basic vehicle. The driver behaviour can be controlled by firstly removing the tolerances from the driver’s aid which it was found improved the precision of the CO2 emissions by 43.5% and secondly by recording the throttle pedal movements to enable the validation of test results. Procedural factors, such as tyre pressures can be easily controlled by resisting the temptation to over check and by installing pressure sensing equipment. Using a modern chassis dynamometer with low parasitic losses will make the job of controlling the dynamometer easier, but all dynamometers can be controlled by following the industry standard quality assurance procedures and implementing statistical process control tools to check the key results. The implementation of statistical process control alone improved the precision of unloaded dynamometer coastdown checks by reducing the coefficient of variation from 6.6 to 4.0%. Using the dynamometer to accelerate the vehicle before coastdown checks was found to approximately halve the variability in coastdown times. It was also demonstrated that verification of the dynamometer inertia simulation and response time are both critically important, as the industry standard coastdown test is insufficient, in isolation, to validate the loading on a vehicle. Six sigma and statistical process control techniques have shown that for complex multiple input single output systems, such as chassis dynamometer fuel economy tests, it is insufficient to improve only one input to the system to achieve a change to the output. As a result, suggested improvements in each noise factor often have to be validated against an input metric rather than the output CO2 emissions. Despite this, the overall level of precision of the CO2 emissions and fuel consumption seen at the start of the research, measured by the coefficient of variation of approximately 2.6%, has been improved by over six times through the simultaneous implementation of the findings from this research with the demonstration of coefficient of variation as low as 0.4%. Through this research three major contributions have been made to the state of the art. Firstly, from the work on driver behaviour an extension is proposed to the Society of Automotive Engineers J2951 drive quality metric standard to include the a newly developed Cumulative Absolute Speed Error metric and to suggest that metrics are reviewed across the duration of a test to identify differences in driving behaviours during a test that do not cause a change to the end of test result. Secondly, the need to instrument the vehicle and test cell to record variability in the key noise factors has been demonstrated. Thirdly, a universal method has been developed and published from this research, to use response modelling techniques for the validation of test repeatability and the correction of CO2 emissions. The impact of these contributions is that the precision of chassis dynamometer emissions tests can be improved by a factor of 6.5 and this is of critical importance as the new real world driving and world light-duty harmonised emissions legislation comes into force over the next two to five years. This legislation will require an unprecedented level of precision for the effective testing of full vehicle system interactions over a larger operating range but within a controlled laboratory environment. If this level of precision is not met then opportunities to reduce vehicle fuel consumption through technology that only has a small improvement on fuel consumption, which is likely given the large advances that have be achieved over the last few decades, will be missed.

När en lastbil färdas på väg utsätts den för ett antal krafter. Däckens rullmotstånd utgör ungefär 36 till 60 % av färdmotståndet. Att kunna validera rullmotståndet vid egen testning är värdefullt för en fordonstillverkare som Scania. Däcktillverkare tillhandahåller en konstant rullmotståndskoefficient men det är oklart om den går att använda i beräkningar för Scanias testsetup.Provningen går ut på att undersöka om testuppställningen möjliggör uppmätning av däckens rullmotstånd på chassidynamometer med momentnav. För den experimentella delen av examensarbetet har en kvantitativ datainsamlingsmetod använts för vidare maskinell analys och manuellt utföra statistisk undersökning. Testdriven utveckling (TDD) har tillämpats för att utifrån testresultaten kunna arbeta iterativt.Vid testningen går rullmotståndskoefficienten upp, ner eller ligger stabilt. Detta beror på att Kistler (Kistler momentnav består av två fälgar som innehåller universalsensorer för att kunna mäta vridmoment) har elektrisk drift som korrelerar till spridning av uppmätt rullmotståndskoefficient. Kistler momentnav är inte repeterbart på grund av drift. Det är möjligt att kompensera för den elektriska driften i Kistler momentnav och beräkna rullmotståndskoefficienten baserat på sista analyspunkten från körningarna.Mätvärden från Kistler momentnav har spridning. Genom att beräkna medelvärde för rullmotståndskoefficienten fås bättre noggrannhet. Medelvärde indikerar att rullmotståndskoefficienten har inget eller litet hastighetsberoende.Det går att använda Kistler momentnav och chassidynamometer 2 som testuppställning för att mäta upp av däckens rullmotståndkoefficient. Det är möjligt för Scania att fortsätta använda denna testuppställning för att bland annat undersöka fler däck. / When a long haul truck travels on a road it’s subjected to a number of forces. The tires rolling resistance is approximately 36 to 60% off the total travel resistance. Being able validate the rolling resistance during own testing is valuable to vehicle manufacturers like Scania. The tire manufacturers provide a constant rolling resistance coefficient but it’s unclear if it can be used in calculations for Scanias test setup.The purpose of the testing is to investigate if the test setup enables measuring the tires rolling resistance on a chassis dynamometer with torque wheels. For the experimental part of the degree project, a quantitative data collection methodology has been used for further machine analyzation and manually performing statistical analysis. Test driven development (TDD) has been applied to work iterative based on the test results.During testing the value of the rolling resistance coefficient went up, down or was stable. This is dependent on the electrical drift Kistler have (Kistler torque wheel consists of two rims that contain universal sensors to measure torque), that correlated with the distribution of the measured rolling resistance coefficient. It’s possible to compensate for the electrical drift in Kistler torque wheel and calculate the rolling resistance coefficient based on the last analyzation point from the tests.The measurements from Kistler torque wheel are distributed. By calculating the average of the rolling resistance coefficients a higher degree of accuracy is obtained. The average indicates that the rolling resistance coefficient have no or a small speed dependency.It’s possible to use Kistler torque wheel and chassis dynamometer 2 as a test setup to measure the rolling resistance of the tires. It’s possible for Scania to continue using this test setup to investigate more tires.

No description available.

With increasing costs of fossil fuels and intensified environmental awareness, low carbon vehicles, including hybrid electric vehicles (HEVs), are becoming more popular for car buyers due to their lower running costs. HEVs are sensitive to the driving conditions under which they are used however, and real-world driving can be very different to the legislative test cycles. On the road there are higher speeds, faster accelerations and more changes in speed, plus additional factors that are not taken into account in laboratory tests, all leading to poorer fuel economy. Future trends in the automotive industry are predicted to include a large focus on increased hybridisation of passenger cars in the coming years, so this is an important current research area. The aims of this project were to determine the energy consumption of a HEV in real-world driving, and investigate the differences in this compared to other standard drive cycles, and also compared to testing in laboratory conditions. A second generation Toyota Prius equipped with a GPS (Global Positioning System) data logging system collected driving data while in use by Loughborough University Security over a period of 9 months. The journey data was used for the development of a drive cycle, the Loughborough University Urban Drive Cycle 2 (LUUDC2), representing urban driving around the university campus and local town roads. It will also have a likeness to other similar driving routines. Vehicle testing was carried out on a chassis dynamometer on the real-world LUUDC2 and other existing drive cycles for comparison, including ECE-15, UDDS (Urban Dynamometer Driving Schedule) and Artemis Urban. Comparisons were made between real-world driving test results and chassis dynamometer real-world cycle test results. Comparison was also made with a pure electric vehicle (EV) that was tested in a similar way. To verify the test results and investigate the energy consumption inside the system, a Prius model in Autonomie vehicle simulation software was used. There were two main areas of results outcomes; the first of which was higher fuel consumption on the LUUDC2 compared to other cycles due to cycle effects, with the former having greater accelerations and a more transient speed profile. In a drive cycle acceleration effect study, for the cycle with 80% higher average acceleration than the other the difference in fuel consumption was about 32%, of which around half of this was discovered to be as a result of an increased average acceleration and deceleration rate. Compared to the standard ECE-15 urban drive cycle, fuel consumption was 20% higher on the LUUDC2. The second main area of outcomes is the factors that give greater energy consumption in real-world driving compared to in a laboratory and in simulations being determined and quantified. There was found to be a significant difference in fuel consumption for the HEV of over a third between on-road real-world driving and chassis dynamometer testing on the developed real-world cycle. Contributors to the difference were identified and explored further to quantify their impact. Firstly, validation of the drive cycle accuracy by statistical comparison to the original dataset using acceleration magnitude distributions highlighted that the cycle could be better matched. Chassis dynamometer testing of a new refined cycle showed that this had a significant impact, contributing approximately 16% of the difference to the real-world driving, bringing this gap down to 21%. This showed how important accurate cycle production from the data set is to give a representative and meaningful output. Road gradient was investigated as a possible contributor to the difference. The Prius was driven on repeated circuits of the campus to produce a simplified real-world driving cycle that could be directly linked with the corresponding gradients, which were obtained by surveying the land. This cycle was run on the chassis dynamometer and Autonomie was also used to simulate driving this cycle with and without its gradients. This study showed that gradient had a negligible contribution to fuel consumption of the HEV in the case of a circular route where returning to the start point. A main factor in the difference to real-world driving was found to be the use of climate control auxiliaries with associated ambient temperature. Investigation found this element is estimated to contribute over 15% to the difference in real-world fuel consumption, by running the heater in low temperatures and the air conditioning in high temperatures. This leaves a 6% remainder made up of a collection of other small real-world factors. Equivalent tests carried out in simulations to those carried out on the chassis dynamometer gave 20% lower fuel consumption. This is accounted for by degradation of the test vehicle at approximately 7%, and the other part by inaccuracy of the simulation model. Laboratory testing of the high voltage battery pack found it constituted around 2% of the vehicle degradation factor, plus an additional 5% due to imbalance of the battery cell voltages, on top of the 7% stated above. From this investigation it can be concluded that the driving cycle and environment have a substantial impact of the energy use of a HEV. Therefore they could be better designed by incorporating real-world driving into the development process, for example by basing control strategies on real-world drive cycles. Vehicles would also benefit from being developed for use in a particular application to improve their fuel consumption. Alternatively, factors for each of the contributing elements of real-world driving could be included in published fuel economy figures to give prospective users more representative values.

Made available in DSpace on 2014-12-17T14:58:06Z (GMT). No. of bitstreams: 1 GilCL_DISSERT.pdf: 1771464 bytes, checksum: 92ddc93639f74d5c2bbc96617815f7ed (MD5) Previous issue date: 2010-12-18 / Flex-fuel vehicles are equipped with Otto Cycle internal combustion engines and have the capability of functioning with more than one type of fuel, mixed at the same tank and burned in the combustion chamber simultaneously. This sort of motorization is a world pattern due to the scarcity of petroleum, the trade of several types of fuels, technology advances and the restriction imposed to gas emissions to the atmosphere. In Brazil, the Flexfuel vehicles are a reality, specially the ones using fuel with 20 to 25% anhydrous alcohol mixed with gasoline and those that use natural gas or original liquid fuel (gasoline or hydrated ethanol). The Brazilian model Fiat Siena, the object of this present scientific investigation, is equipped with a unique electronic central capable of managing the liquid or gaseous fuels. The purpose of this research was to perform a comparative analysis in terms of performance (in terms of both potency and consumption) of a tetra-fuel vehicle - using a chassis dynamometer, operating with different fuels: common gasoline, premium gasoline, Podium gasoline, ethanol or natural gas. It became necessary to develop a bench of tests and trials procedures, as well as to know the functioning of the electronic management of the vehicle under analysis. The experiments were performed at the automotive laboratory in CTGAS-ER (Center of Gas Technologies and Renewable energies) at the light of Brazilian standard ABNT, NBR 7024: Light on-road vehicles - measurement of fuel consumption. The essay results on specific fuel consumption using common gasoline, premium gasoline and Podium gasoline have shown similar results, both for urban and road driving cycles / Os ve?culos flex s?o equipados com um motor de combust?o interna do ciclo Otto e t?m como caracter?stica a capacidade de funcionar com mais de um tipo de combust?vel, misturados no mesmo tanque e queimados na c?mara de combust?o simultaneamente. Este tipo de motoriza??o ? uma tend?ncia mundial devido ? escassez do petr?leo, a comercializa??o de v?rios tipos de combust?veis, aos avan?os tecnol?gicos dos sistemas de gerenciamento eletr?nico de combust?vel e ?s restri??es as emiss?es de gases poluentes na atmosfera. No Brasil, os ve?culos flex s?o uma realidade, com destaque para os ve?culos alimentados com 20 a 25% do ?lcool anidro misturado com gasolina e os que utilizam g?s natural ou o combust?vel l?quido original (gasolina ou etanol hidratado). O FIAT SIENA TETRAFUEL, objeto da presente investiga??o, ? equipado com uma ?nica central eletr?nica capaz de gerenciar os combust?veis l?quidos ou gasoso. A pesquisa em tela teve como prop?sito a an?lise comparativa de desempenho (pot?ncia e consumo) de um ve?culo tetracombust?vel simulando ciclos de condu??o urbano e de estrada em um dinam?metro de chassi, operando com os combust?veis: gasolina comum (tipo C), gasolina aditivada (tipo C), gasolina Podium (Premium), etanol (AEHC) ou g?s natural (GNV). Foi necess?rio desenvolver bancada de testes e procedimentos de ensaios, como tamb?m conhecer o funcionamento do gerenciamento eletr?nico do ve?culo em quest?o. Os ensaios foram realizados no Laborat?rio do Centro de Tecnologias do G?s e Energias Renov?veis de acordo com a norma ABNT NBR 7024 - Ve?culos rodovi?rios leves Medi??o do consumo de combust?vel. Os resultados dos ensaios de consumo espec?fico com as gasolinas comum, aditivada e Podium resultaram em valores pr?ximos, tanto no ciclo de condu??o urbano como tamb?m no ciclo de condu??o de estrada

[pt] O desempenho de veículos automotivos é um importante atributo a ser avaliado quando motores de combustão interna e novos combustíveis estão sendo desenvolvidos. A previsão desse parâmetro também é de suma importância, uma vez que os testes de desempenho de automóveis em pista requerem prazos de realização e altos custos com equipamentos, aluguel da pista, contratação de pessoas e deslocamento de veículos e combustíveis. Além disso, seus resultados são diretamente afetados por irregularidades na superfície da pista e variações nas condições climáticas, como pressão ambiente, temperatura, umidade do ar e velocidade do vento. Assim, este trabalho tem como objetivo utilizar os dados coletados em testes de bancada com um motor de combustão interna com a finalidade de modelar os testes de retomada de velocidade de um automóvel convencional leve. A metodologia proposta simula a força de tração nas rodas a partir do torque medido no dinamômetro do motor ou a partir das curvas de pressão no interior da câmara de combustão com o auxílio de modelos de atrito para motores de ignição por centelha. Para validar o modelo proposto, foi necessário realizar testes de retomada de velocidade com o carro em um dinamômetro de chassi. Além disso, foram utilizadas sete misturas diferentes de etanol e gasolina, e concluiu-se que o etanol anidro puro promoveu maior capacidade de aceleração na maioria dos experimentos, mas apresentou maior consumo de combustível. Os combustíveis hidratados reduziram o desempenho, mas melhoraram a eficiência global. As simulações demonstraram alta precisão em relação ao experimento, com média da diferença do tempo de recuperação da velocidade de 0,51 segundos e desvio padrão de 0,078. Além disso, as simulações de desempenho de aceleração tiveram erros menores que 5,25 por cento. Além disso, a realização desses testes em laboratório tem a vantagem de um maior controle das condições ambientais da sala e dos parâmetros de operação do motor. / [en] Vehicle performance is an important feature to be evaluated when internal combustion engines and new fuels are being developed. Predicting this parameter is also of great significance, once track testing requires long periods of time to be done and high costs with equipment, rental of the track, hiring people and displacement of vehicles and fuels. In addition, their results are directly affected by track surface irregularities and variations in weather conditions such as ambient pressure, temperature, air humidity and wind speed. Thus, this work aims to use collected data in bench tests with an internal combustion engine in order to modeling an automobile speed recovery time. The proposed methodology simulates the traction force on the wheels based on the measured torque in engine dynamometer or from the pressure curves inside the combustion chamber with the aid of friction models for spark ignition engines. In order to validate the proposed model, it became necessary to perform speed recovery tests with the car on a chassis dynamometer. Also, seven different mixtures of ethanol and gasoline were used, and it was concluded that pure anhydrous ethanol promoted a higher acceleration capacity in most of the experiments but it had higher fuel consumption. Hydrated fuels reduced performance but improved global efficiency. The simulations demonstrated a high precision in relation to the experiment, with a speed recovery time diference average of 0.51 seconds and standard deviation of 0.078. Also, the acceleration performance simulations had errors smaller than 5.25 percent. In addition, doing these tests in laboratory has the advantage of a greater control of the room ambient conditions and the engine operating parameters.