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Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

The world of automotive engineering shows a clear direction for upcoming development trends. Stringent fleet average fuel consumption targets and CO2 penalties as well as rising fuel prices and the consumer demand to lower operating costs increases the engineering efforts to optimize fuel economy. Passenger car engines have the benefit of higher degree of technology which can be utilized to reach the challenging targets. Variable valve timing, downsizing and turbo charging, direct gasoline injection, highly sophisticated operating strategies and even more electrification are already common technologies in the automotive industry but can not be directly carried over into a motorcycle application. The major differences like very small packaging space, higher rated speeds, higher power density in combination with lower production numbers and product costs do not allow implementation such high of degree of advanced technology into small-engine applications.

Vehicle driveability evolves more and more as a key decisive factor for marketability and competitiveness of passenger cars, since the final decision of customers to buy a car is usually taken after a more or less intensive test drive. Car manufacturers currently evaluate vehicle driveability with subjective assessments and by having their experienced test drivers fill out form sheets. These assessments are time and cost intensive, limited in repeatability and not objective. The real customer requirements cannot be recognized in detail with this method. This paper describes a completely new approach for an objective and real time evaluation of relevant driveability criteria, for use in a vehicle and on a high dynamic test bed. The vehicle application enables an objective comparison between vehicles and an application as a development tool in many development and calibration phases, where ever fast and objective driveability results are required.

The reduction of nitrous oxides in the exhaust gases of internal combustion engines using a urea water solution is gaining more and more importance. While maintaining the future exhaust gas emission regulations, like the Euro 6 for passenger cars and the Euro 5 for commercial vehicles, urea dosing allows the engine management to be modified to improve fuel economy as well. The system manufacturer Robert Bosch has started early to develop the necessary dosing systems for the urea water solution. More than 300.000 Units have been delivered in 2007 for heavy duty applications. Typical dosing quantities for those systems are in the range of 0.01 l/h for passenger car systems and up to 10 l/h for commercial vehicles. During the first years of development and application of urea dosing systems, instantaneous flow measuring devices were used, which were not operating fully satisfactory.

The incorporation of a detailed engine process calculation that takes into account thermal behavior of the engine and exhaust system is essential for a realistic simulation of transient vehicle operation. This is the only possible way to have a precise preliminary calculation of fuel consumption and emissions. Therefore, a comprehensive thermal network of the engine based on the lumped capacity method has been developed. The model allows the computation of component temperatures in steady state operation as well as in transient engine studies, e.g. investigations of engine warm-up. The model is integrated in a co-simulation environment consisting of a detailed vehicle and engine cycle simulation code. The paper describes the procedure of the co-simulation and presents several examples of warm-up simulations.

The well-to-wheel CO2 emissions and energy use of internal combustion engines (diesel and gasoline) are compared to fuel cell automotive propulsion systems. The fuel cell technologies investigated are polymer electrolyte fuel cell (PEFC), alkaline fuel cell (AFC) and solid oxide fuel cell (SOFC). The fuels are assumed to be produced from either crude oil or natural gas. The comparison is based on driving cycle simulations of a mid-class passenger car with an inertia test weight of 1350 kg. The study shows that the optimized diesel drive train (downsized mated to an integrated starter generator) achieves the best overall energy efficiency. The lowest CO2 emissions are produced by compressed natural gas (CNG) vehicles. Fuel cell propulsion systems achieve similar or even better CO2 emission values under hot start conditions but suffer from high energy input required during warm-up.

In order to improve the accuracy of vehicle simulation under transient cycle conditions and thus predict performance and fuel consumption, consideration of the complete system engine/drivetrain/vehicle is necessary. The coupling of otherwise independent simulation programs is therefore necessary for the vehicle and engine. The description of thermally transient processes enables the calculation of the heat balance of the engine, which in turn enables the simulation of warming up operation. Through consideration of the engine warming up process, the quality of the prediction of fuel consumption and emissions is improved. The combination of the simulation programs CRUISE and BOOST to determine the engine heat balance has proven to be successful for the analysis of transient drive cycles.

The paper gives an overview of the partially extremely complex problem when looking into commonalities and differences of the three main application areas of engines and powertrains - automotive, agricultural tractors, and industrial engines, the last being predominantly but not exclusively focused on construction equipment. The modern “platform” approach has been used in the automotive world to a large extent and the learned experiences may be of interest for the agricultural tractors and/or the construction equipment manufacturers. On the other hand the truck engine engineers and manufacturers will learn more about the special requirements of the tractor and the industrial engines fields, and thus influence concepts and development procedures and also the production of the automotive engines which in many cases serve as the basis for derivate engines.

The paper describes a feasibility test program on a 2 liter, 4 cylinder DI/TCI passenger car engine operated on the new alternative fuel Dimethyl Ether (DME, CH3 - O - CH3) with the aim of demonstrating its potential of meeting ULEV emissions (0.2 g/mi NOx in the FTP 75 test cycle) when installed in a full size passenger car. Special attention is drawn to the fuel injection equipment (FIE) as well as combustion system requirements towards the reduction of NOx and combustion noise while keeping energetic fuel consumption at the level of the baseline DI/TCI diesel engine. FIE and combustion system parameters were optimized on the steady state dynamometer by variation of a number of parameters, such as rate of injection, number of nozzle holes, compression ratio, piston bowl shape and exhaust gas recirculation.

This paper presents an overview of the results on heavy duty engines collected in the “PARTICULATES” project, which aimed at the characterization of exhaust particle emissions from road vehicles. The same exhaust gas sampling and measurement system as employed for the measurements on light duty vehicles [1] was used. Measurements were made in three labs to evaluate a wide range of particulate properties with a range of heavy duty engines and fuels. The measured properties included particle number, with focus separately on nucleation mode and solid particles, particle active surface and total mass. The sample consisted of 10 engines, ranging from Euro-I to prototype Euro-V technologies. The same core diesel fuels were used as in the light duty programme, mainly differentiated with respect to their sulphur content. Additional fuels were tested by some partners to extend the knowledge base.

The requirement for increased power and reduced emission and fuel consumption levels for diesel engines has created very stringent demands on the cylinder head design. In current engine development programs it is often observed that the limiting design factor is given by the thermal mechanical fatigue strength of the cylinder head. Design iterations resulting from durability testing are often necessary due to the lack of adequate simulation techniques for prediction thermal mechanical fatigue (TMF) failure. A complete lifetime simulation process is presented in this paper with emphasis on a newly developed material model for describing the constitutive behavior of cast iron (i.e. gray cast iron and compacted graphite iron) under thermal cycling. The material model formulation is based on a continuum-damage-mechanics (CDM) approach in order to account for the tension / compression anomaly of cast iron.

The rapidly growing complexity and the growing cross linking of powertrain components leads to longer development times, especially in the vehicle calibration process. The number of systems which need to be fitted to each other and the number of parameters to be calibrated in the particular systems are increasing tremendously. The extensive use of simulation promises to reduce the calibration effort by providing pre-optimized parameter sets. This paper describes a new simulation methodology by the interlinking of advanced vehicle simulation and evaluation tools, in particular the AVL-tools CRUISE, VSM and DRIVE. This methodology allows to semi automatically pre-optimize powertrain and vehicle parameters before hardware is involved. So far the pre-calibration of vehicle and powertrain parameters by simulation was not satisfying because of the missing of a reliable evaluation tool for the produced simulation results.

For the development of complex control algorithms and strategies the engine and powertrain test bed offers a number of advantages over the development in the prototype vehicle. The paper discusses how state-of-the-art simulation techniques can contribute to a continuous development process, which is based upon offline simulation using hardware in the loop, the utilization of modern test bed technology up to vehicle adjustment. The integration of hardware-in-the-loop testing together with vehicle and transmission simulation on the testbed allows to speed up the optimization of fuel consumption, emissions and driveability in an early stage in the development process. The available software tools are presented and application examples are given.

Best fuel efficiency is one of the core requirements for commercial vehicles in India. Consequently it is a central challenge for commercial vehicle OEMs to optimize the entire powertrain, hence match engine, transmission and rear axle specifications best to the defined application. The very specific real world driving conditions in India (e.g. traffic situations, road conditions, driver behavior, etc.) and the large number of possible commercial powertrain combinations request an efficient and effective development methodology. This paper presents a methodology and tool chain to specify and develop commercial powertrains in a most efficient and effective way. The methodology is based on the measurement of real world driving scenarios, identification of representative Real World Driving Profiles and vehicle system simulation which allows extended analysis of the road topography, the traffic situation as well as the driver behavior.

Increasing powertrain complexity and the growing number of vehicle variants are putting a strain on current calibration development processes. This is particularly challenging for vehicle drivability calibration, which is traditionally completed late in the development cycle, only after mature vehicle hardware is available. Model-based calibration enables a shift in development tasks from the real world to the virtual world, allowing for increased system robustness while reducing development costs and time. A unique approach for drivability calibration was developed by incorporating drivability analysis software with online optimization software into a virtual engine test cell environment. Real-time, physics-based engine and vehicle simulation models were coupled with real engine controller hardware and software to execute automated drivability calibration within this environment.

With the increased number of variants, the preservation of a brand-specific vehicle DNA becomes more and more important. Paired with growing customer expectations, brand DNA can be a crucial point in the decision-making process of buying a new vehicle. Whereas the customer will assess the DNA subjectively during driving by evaluating the vehicle drive quality (“driveability”), most manufacturers are not merely relying on subjective evaluations by having test drivers perform maneuvers with prototype vehicles. Nowadays, the assessment is performed objectively during the vehicle development process. As a supporting measure, the Anstalt für Verbrennungskraftmaschinen List (AVL) has made the objective assessment tool AVL-DRIVE commercially available. Up to now, the AVL-DRIVE ratings had to be manually analyzed and checked for outliers. Low ratings and high deviations to a priori specified target values are a good starting point for the search of outliers.

On the path to decarbonizing road transport, electric commercial vehicles will play a significant role. The first applications were directed to the smaller trucks for distribution traffic with relatively moderate driving and range requirements, but meanwhile, the first generation of a complete portfolio of truck sizes is developed and available on the market. In these early applications, many compromises were accepted to overcome component availability, but meanwhile, the supply chain can address the specific needs of electric trucks. With that, the optimization towards higher usability and lower costs can be moved to the next level. Especially for long-haul trucks, efficiency is a driving factor for the total costs of ownership. Besides the propulsion system, all other systems must be optimized for higher efficiency. This includes thermal management since the thermal management components consume energy and have a direct impact on the driving range.