Search Results

Discussions about the optimal technology of propulsion systems for future ground vehicles have been raising over the last few years. Several options include different types of technologies. However, those who are advocating conventional internal combustion engines are faced with the fact that fossil fuels are limited. Others favor hydrogen fuel as the solution for the future, either in combination with combustion engines or as an energy carrier for fuel cells. In any case, the production and storage of hydrogen is an ongoing challenge of numerous research works. Finally, there are battery-electric or hybrid propulsion systems in use, gaining more and more popularity worldwide. Ongoing advances in power electronics help to improve control systems within automotive applications. New developed or designed components enable more efficient system architectures and control.

Automotive embedded systems have become very complex, are strongly integrated, and the safety-criticality and real-time constraints of these systems raise new challenges. The OSEK/VDX standard provides an open-ended architecture for distributed real-time capable units in vehicles. This is supported by the OSEK Implementation Language (OIL), a language aiming at specifying the configuration of these real-time operating systems. The challenge, however, is to ensure consistency of the concept constraints and configurations along the entire product development. The contribution of this paper is to bridge the existing gap between model-driven systems engineering and software engineering for automotive real-time operating systems (RTOS). For this purpose a bidirectional tool bridge has been established based on OSEK OIL exchange format files.

Nowadays, investigating underhood airflow by using numerical simulation is a standard task in the development process of passenger cars and commercial vehicles. Numerous publications exist which deal with simulating the airflow through the engine compartment of road vehicles. However, hardly anything can be found which deals with off-road vehicles and nothing exists which focuses on snowmobiles. In the presented paper the airflow and the thermal conditions inside the engine compartment of a snowmobile are investigated by the usage of computational fluid dynamics (CFD) as well as experimental methods. Field tests at arctic conditions have been conducted on a serial snowmobile to measure temperatures inside the compartment and to gain realistic boundary conditions for the numerical simulation. Thermocouples (type K) were attached under the hood to measure exhaust, air, coolant and surface temperatures of several components at previously defined load cases.

The enhancement of efficiency will play a more and more important role in the development of future (small) internal combustion engines. In recent years, the Atkinson (or Extended Expansion) cycle, realized over the crank drive, attracted increasing attention. Several OEMs have investigated this efficiency-increasing principle in the whole range from small engines up to automotive engines until now. In prior publications, the authors outlined the remarkable efficiency potentials of an Extended Expansion (EE) cycle. However, for an internal combustion engine, a smooth running performance as well as low vibrations and noise emissions are relevant aspects. This is especially true for an Extended Expansion engine realized over the crank drive. Therefore, design measures concerning friction and NVH need to be taken to enable possible series production status. Basically, these measures strongly depend on the reduction of the free mass forces and moments.

Due to current progresses in the field of driver assistance systems and the continuously growing electrification of vehicle drive trains, the evaluation of driver behavior has become an important part in the development process of modern cars. Findings from driver analyses are used for the creation of individual profiles, which can be permanently adapted due to ongoing data processing. A benefit of data-based dynamic control systems lies in the possibility to individually configure the vehicle behavior for a specific driver, which can contribute to increasing customer acceptance and satisfaction. In this way, an optimization of the control behavior between driver and vehicle and the resulting mutual system learning and -adjustment hold great potential for improvements in driving behavior, safety and energy consumption.

The automotive domain has seen safety engineering at the forefront of the industry’s priorities for the last decade. Therefore, additional safety engineering efforts, design approaches, and well-established safety processes have been stipulated. Today many connected and automated vehicles are available and connectivity features and information sharing are increasingly used. This increases the attractiveness of an attack on vehicles and thus introduces new risks for vehicle cybersecurity. Thus, just as safety became a critical part of the development in the late 20th century, the automotive domain must now consider cybersecurity as an integral part of the development of modern vehicles. Aware of this fact, the automotive industry has, therefore, recently taken multiple efforts in designing and producing safe and secure connected and automated vehicles.

In order to fulfill future regulations regarding emissions and CO2 reduction, the small engine market inclines to migrate from carburetor systems to cleaner, more efficient electronic ignition controls and electronic fuel injection systems. When implementing such mechatronic systems in small engine applications, one has to consider specific boundary conditions like the lack of relevant sensors, limited possibilities in terms of space and of course the necessity to keep the costs as low as possible. Especially in the non-road mobile machinery (NRMM) segment, the absence of sensors makes it difficult to apply standard electronic control systems, which are based on engine related input signals provided by sensors. One engine related signal, which is even provided by the simplest engine setup, is some form of the crankshaft speed since it is essential for the functionality of the engine.

The release of the “Regulation No. 168/2013” for the approval and market surveillance of two- or three-wheel motorcycles and quadricycles of the European Union started a new challenge for the motorcycle industry. One goal of the European Union is to achieve emission parity between passenger cars (EURO 6) and motorcycles (EURO 5) in 2020. The hybridization of motorcycle powertrains is one way to achieve these strict legislation limits. In the automotive sector, hybridization is well investigated and has already shown improvements of fuel consumption, efficiency and emission behavior. Equally, motorcycle applications have a high potential to improve efficiency and to meet customer needs as fun to drive as well. This paper describes a methodical approach to analyze conventional motorcycles regarding the energy and power demand for different driving cycles and driving conditions. Therefore, a dynamic or forward vehicle simulation within MATLAB Simulink is used.

A worldwide decrease of legal limits for CO2 emissions and fuel economy led to stronger efforts for achieving the required reductions. The task is to evaluate technologies for CO2 reduction and to define a combination of such measures to ensure the targets. The challenge therefor is to find the optimal combination with respect to minimal costs. Individual vehicles as well as the whole fleet have to be considered in the cost analysis - which raises the complexity. Hereby, the focus of this work is the consideration and improvement of a new model series against the background of a fleet and the selection of measures. The ratio between the costs and the effect of the measures can be different for the each vehicle configuration. Also, the determination of targets depends whether a fleet or an individual vehicle is selected and has impact on the selection and optimization process of those measures.

Aircraft engines in the (ELA1) category, with a maximum power of up to 100kW, are characterized by a verified state of the art technology. New developments of engine technologies and control methods are very slowly being introduced into this engine segment. This trend is based on the fact that new technologies implemented in aircraft engines must be thoroughly certified and validated in a very complex and documented procedure. For this reason, most of the engines in this class are equipped with a carburetor as an air/fuel mixture preparation system. Moreover, naturally aspirated spark ignited engines are widely used in the aircraft category, with a take-off weight of up to 1000kg.

Aiming at the test safety problems in the early stage of self-driving cars development, firstly the virtual vehicle on-board CAN data acquisition module of the present project was designed based on virtual LabVIEW. Then a wireless remote control system for the self-driving car was constructed, which integrated the built virtual vehicle on-board CAN data acquisition system, the remote real-time image monitoring module and the remote upper computer control module based on ZigBee wireless transmission. It can execute the environmental awareness training and continuous and complex motion manipulation testing of the vehicle without relying on the driver, which can solve the safety problems in the tests of initial development of self-driving cars. Finally, the four-wheel independent steering electric vehicle was used as the self-driving test vehicle, and the wireless remote control system was tested on the double lane change type path and S-type path.

To increase reliability and the maintenance interval of an internal combustion engine while operating it with the lowest possible emissions, spark plug wear must be reduced. In this context, information about the spark plug center and the ground electrode temperature is key. Several measurement devices have been developed that measure the temperature of spark plug electrodes. The great challenge is to measure the temperature of the center electrode; on the one hand, the measurement device must be insulated and capable of withstanding the high voltage of the ignition system, and on the other hand, the device should not influence the ignition system. All previously studied devices presented in this paper have in common that major reconstruction of the ignition system and/or spark plugs whose design is very different from the standard engine spark plug were necessary.

Measuring emissions of internal combustion engines-not only at steady-state conditions, but also with highly dynamic test cycles-is an important issue in modern engine development. Due to the fact that ambient conditions have an essential influence on power and emissions of internal combustion engines, test beds used for such measurements typically incorporate intake air and exhaust back pressure control for reasons of repeatability, accuracy and comparability. As test cycle dynamics get faster and legal pressure tolerances get narrower, pressure control becomes more demanding and simple PI control schemes are pushed to their limits; therefore, more sophisticated control schemes are necessary. In this paper, a linearised model is first derived and then used to both simplify and optimise PI controller tuning. This is done by means of frequency domain methods. Limitations to such controllers and possible approaches to overcome them are discussed.

As the number of different engine and vehicle concepts for powered-two wheelers is very high and will even rise with hybridization, the simulation of emissions and fuel consumption is indispensable for further development towards more environmentally friendly mobility. In this work, an adaptive artificial neural network based predictive model for emission and fuel consumption simulation of motorcycles operated in real world conditions is presented. The model is developed in Matlab and Simulink and is integrated into a longitudinal vehicle dynamic simulation whereby it is possible to simulate various and not yet measured test cycles. Subsequently, it is possible to predict real drive emissions RDE and on-road fuel consumption by a minimum of previous measurement effort.

A reduction in CO2 emissions and consequently fuel consumption is essential in the context of future greenhouse gas limits. With respect to the thermodynamic loss analysis of an internal combustion engine, a gap between the net indicated thermal efficiency and the brake thermal efficiency is recognizable. This share is caused by friction losses, which are the focus of this research project. The parasitic loss reduction potential by replacing the mechanical water pump with an electric coolant pump is discussed in the course of this work. This is not a novel approach in light duty vehicles, whereas in commercial vehicles a rigid drive of all auxiliaries is standard. Taking into account an implementation of a 48-V power system in the short or medium term, an electrification of auxiliary components becomes feasible. The application of electric coolant pumps on an Euro VI certified 6-cylinder in-line heavy-duty diesel engine regarding fuel economy was thus performed.

Hybrid electric vehicles (HEVs) with a power-split system offer a variety of possibilities in reduction of CO2 emissions and fuel consumption. Power-split systems use a planetary gear sets to create a strong mechanical coupling between the internal combustion engine, the generator and the electric motor. This concept offers rather low oscillations and therefore passive damping components are not needed. Nevertheless, during acceleration or because of external disturbances, oscillations which are mostly influenced by the ICE, can still occur which leads to a drivability and performance downgrade. This paper proposes a design of an active damping control system which uses the electric motor to suppress those oscillations instead of handling them within the ICE control unit. The control algorithm is implemented as part of an existing hybrid controller without any additional hardware introduced.

Given approximately one million small and light aircraft in operation worldwide, icing detection and icing quantification of in-flight icing are still an open research topic. Despite technical means are available to de-ice on ground, there is a lack of a suitable control system based on sensor data to de-ice while the aircraft is airborne. Most often, it is still task of the pilot to visually inspect the icing status of the airfoil and/or other critical parts of the aircraft such as engine air intakes, which distracts the flight crew from flying the aircraft especially in IMC conditions. Based on preliminary simulation and tests in 2014 in a collaborative research project lasting from 2015 until 2018, the technology of energy self-sustaining, wireless, self-adhesive smart sensors for industrial sensing in an aerodynamically critical environment (i.e. wind turbines) was further investigated to fulfil general aviation requirements.

As a result of the ever-increasing application of cyber-physical components in the automotive industry, cybersecurity has become an urgent topic. Adapting technologies and communication protocols like Ethernet and WiFi in connected vehicles yields many attack scenarios. Consequently, ISO/SAE 21434 and UN R155 (2021) define a standard and regulatory framework for automotive cybersecurity, Both documents follow a risk management-based approach and require a threat modeling methodology for risk analysis and identification. Such a threat modeling methodology must conform to the Threat Analysis and Risk Assessment (TARA) framework of ISO/SAE 21434. Conversely, existing threat modeling methods enumerate isolated threats disregarding the vehicle’s design and connections. Consequently, they neglect the role of attack paths from a vehicle’s interfaces to its assets.

The current European fleet of vehicles is ageing and lifetime mileages are rising proportionally. Consequently, a substantial fraction of the vehicle fleet is currently operating at mileages well beyond current durability legislation (≤ 160,000 km). Emissions inventories and models show substantial increases in emissions with increasing mileage, but knowledge of the effect of emissions control system deterioration at very high mileages is sparse. Emissions testing has been conducted on matched pairs (or more) of diesel and gasoline (and CNG) vehicles, of low and high mileage, supplementing the results with in-house data, in order to explore high mileage emission deterioration factors (DF). The study isolated, as far as possible, the effect of emissions deterioration with mileage, by using nominally identical vehicle models and controlling other variables.

The replacement of safety-critical mechanical components with electro-mechanical systems has led to the fact that safety aspects play a central role in development of embedded automotive systems. Recently, consumer demands for connectivity (e.g., infotainment, car-2-car or car-2-infrastructure communication) as well as new advances toward advanced driver assistance systems (ADAS) or even autonomous driving functions make cybersecurity another key factor to be taken into account by vehicle suppliers and manufacturers. Although these can capitalize on experiences from many other domains, they still have to face several unique challenges when gearing up for specific cybersecurity challenges. A key challenge is related to the increasing interconnection of automotive systems with networks (such as Car2X). Due to this connectivity, it is no longer acceptable to assume that safety-critical systems are immune to security risks.