Automotive and Engine Technology最新文献

The development of innovative powertrain technologies is crucial for car manufacturers to comply with decreasing (hbox {CO}_2) emission limits. They face the challenge to develop products which fulfill customer requirements in terms of functionality, comfort and cost but also provide a significant (hbox {CO}_2) efficiency improvement. ({48}hbox { V})-hybrids can achieve these conflicting goals due to their low vehicle-integration effort and system costs while substantially increasing powertrain efficiency. The variance of real-driving scenarios has to be considered in system development to achieve the maximum customer benefit with the chosen system design, such as installed electrical power or topology. This paper presents a comprehensive investigation of different ({48}hbox { V})-system designs under real-driving conditions. The influence of varying real-driving scenarios on component load collectives is analyzed for P1 and P2 topologies. Furthermore, the (hbox {CO}_2) reduction potential and the influence of different hybrid functions such as electric driving is identified. The contribution of this paper is the identification of ({48}hbox { V})-system potentials under real-driving conditions and the corresponding component requirements, in order to support the development of customer-oriented ({48}hbox { V})-systems.

Today’s combustion engine development is strongly driven by reduction of (hbox {CO}_2) and exhaust gas emissions. Modern turbocharged downsizing concepts with gasoline direct injection are well established in all major markets and contribute to current and future mobility as a cost attractive and efficient solution. Further improvement of gasoline engine efficiency and performance is mainly limited by knocking. Water injection (WI) has the potential to reduce knocking significantly. To improve the effectiveness of water injection, fundamental knowledge of the thermodynamic process has to be built up. Therefore, a zero dimensional evaporation model was developed and simulations were carried out. This model was derived and validated on the basis of measurements which were carried out on a specifically designed and assembled WI evaporation chamber. Conditions in terms of temperature and pressure were varied to determine the evaporation behaviour of water droplets influenced by temperatures of e.g. air or water. The model describes the process of droplet heating and finally the evaporation of the droplets depending on their size at relevant engine boundary conditions. The simulation results support interpretation of engine measurements and allow further optimization of water injection concepts.

This paper introduces a method for efficiently solving stochastic optimization problems in the field of engine calibration. The main objective is to make more conscious decisions during the base engine calibration process by considering the system uncertainty due to component tolerances and thus enabling more robust design, low emissions, and avoiding expensive recalibration steps that generate costs and possibly postpone the start of production. The main idea behind the approach is to optimize the design parameters of the engine control unit (ECU) that are subject to uncertainty by considering the resulting output uncertainty. The premise is that a model of the system under study exists, which can be evaluated cheaply, and the system tolerance is known. Furthermore, it is essential that the stochastic optimization problem can be formulated such that the objective function and the constraint functions can be expressed using proper metrics such as the value at risk (VaR). The main idea is to derive analytically closed formulations for the VaR, which are cheap to evaluate and thus reduce the computational effort of evaluating the objective and constraints. The VaR is therefore learned as a function of the input parameters of the initial model using a supervised learning algorithm. For this work, we employ Gaussian process regression models. To illustrate the benefits of the approach, it is applied to a representative engine calibration problem. The results show a significant improvement in emissions compared to the deterministic setting, where the optimization problem is constructed using safety coefficients. We also show that the computation time is comparable to the deterministic setting and is orders of magnitude less than solving the problem using the Monte-Carlo or quasi-Monte-Carlo method.

Already enacted carbon-dioxide (CO₂) limiting legislations for passenger cars and heavy duty vehicles, drive motivations to consider electrification also in the sector of non-road mobile machinery. Up to now, only the emissions of the vehicles themselves have been restricted. However, to capture the overall situation, a more global assessment approach is necessary. The study described in this article applies a tank-to-wheel and an extended well-to-wheel approach based on simulations to compare three different powertrains: a battery electric drive, a parallel electric hybrid drive, and a series electric hybrid drive. The results show that electrification is not per se the better solution in terms of keeping CO₂ emissions at a minimum, as battery electric powertrains are accountable for the lowest as well as the highest possible CO₂ emissions of all powertrains compared. A battery electric machine is not economically competitive if its battery has to last a whole working day. Parallel hybrid systems do not achieve much of an advantage in terms of CO₂ emissions. In this global assessment approach, the most promising propulsion system for wheel-driven-mobile-machinery appears to be the series hybrid system, which shows to offer up to 20% of CO₂ saving potential compared to the current machine.

The importance of thermal management has increased with the advent of electrification and fuel cell. The dynamic response required from the thermal circuit has also increased and cannot be reproduced by today’s conditioning systems. This contribution describes a novel, considerably more powerful conditioning concept with three main characteristics:

• The positioning of the control actuator on the side of the unit under test without causing changes in the hydraulic circuit. The exchange of heat in this configuration occurs through mixing.

• Model-based control including improved temperature measurement as the basis for the robust variation of fluid temperature.

• A small and compact design through the consequent optimization of component location. This has the effect of further improving the dynamic response and offers great flexibility in practical use.

The new conditioning concept is validated via simulation as well as by an application on a powertrain test bed. The system proved to be extremely robust in its function due to the consideration of all influencing parameters and, in addition, it is easy to use: no time-consuming configuration work is required prior to installation, nor when changing the test bed or the unit under test. The foundation for this is the model-based control that is based on a direct relationship between the temperature of the medium and the setpoint value. For the first time, temperature traces previously measured under real operation conditions can be reproduced and even temperature gradients of up to 60 K/s can be followed. The dynamic conditioning unit described here will be extended by a transient, real-time capable simulation model to a thermal emulator. This will enable future thermal management functions to be developed and optimized in ThermoLabs.

Validating safety is an unsolved challenge before autonomous driving on public roads is possible. Since only the use of simulation-based test procedures can lead to an economically viable solution for safety validation, computationally efficient simulation models with validated fidelity are demanded. A central part of the overall simulation tool chain is the simulation of the perception components. In this work, a sequential modular approach for simulation of active perception sensor systems is presented on the example of lidar. It enables the required level of fidelity of synthetic object list data for safety validation using beforehand simulated point clouds. The elaborated framework around the sequential modules provides standardized interfaces packaging for co-simulation such as Open Simulation Interface (OSI) and Functional Mockup Interface (FMI), while providing a new level of modularity, testability, interchangeability, and distributability. The fidelity of the sequential approach is demonstrated on an everyday scenario at an intersection that is performed in reality at first and reproduced in simulation afterwards. The synthetic point cloud is generated by a sensor model with high fidelity and processed by a tracking model afterwards, which, therefore, outputs bounding boxes and trajectories that are close to reality.

This paper presents a virtual toolchain for the optimal concept and prototype dimensioning of 48 V hybrid drivetrains. First, this toolchain is used to dimension the drivetrain components for a 48 V P0+P4 hybrid which combines an electric machine in the belt drive of the internal combustion engine and a second electric machine at the rear axle. On an optimal concept level, the power and gear ratios of the electric components in the 48 V system are defined for the best fuel consumption and performance. In the second step, the optimal P0+P4 drivetrain is simulated with a prototype model using a realistic rule-based operating strategy to determine realistic behavior in legal cycles and customer operation. The optimal variant shows a fuel consumption reduction in the Worldwide harmonized Light Duty Test Cycle of 13.6 % compared to a conventional vehicle whereas the prototype simulation shows a relatively higher savings potential of 14.8 %. In the prototype simulation for customer operation, the 48 V hybrid drivetrain reduces the fuel consumption by up to 24.6 % in urban areas due to a high amount of launching and braking events. Extra-urban and highway areas show fuel reductions up to 11.6 % and 4.2 %, respectively due to higher vehicle speed and power requirements. The presented virtual toolchain can be used to combine optimal concept dimensioning with close to reality behaviour simulations to maximise realistic statements and minimize time effort.

Cylinder deactivation is a well-known measure for reducing fuel consumption, especially when applied to gasoline engines. Mostly, such systems are designed to deactivate half of the number of cylinders of the engine. In this study, a new concept is investigated for deactivating only one out of four cylinders of a commercial vehicle diesel engine (“3/4-cylinder concept”). For this purpose, cylinders 2–4 of the engine are operated in “real” 3-cylinder mode, thus with the firing order and ignition distance of a regular 3-cylinder engine, while the first cylinder is only activated near full load, running in parallel to the fourth cylinder. This concept was integrated into a test engine and evaluated on an engine test bench. As the investigations revealed significant improvements for the low-to-medium load region as well as disadvantages for high load, an extensive numerical analysis was carried out based on the experimental results. This included both 1D simulation runs and a detailed cylinder-specific efficiency loss analysis. Based on the results of this analysis, further steps for optimizing the concept were derived and studied by numerical calculations. As a result, it can be concluded that the 3/4-cylinder concept may provide significant improvements of real-world fuel economy when integrated as a drive unit into a tractor.

This paper investigates the local air-to-fuel ratio measurement within the pre-chamber of a spark-ignition engine by determining the absorption of light from hydrocarbons using an infrared sensor. The measurement was performed during fired and motored engine operation points and compared to the more common exhaust lambda measurements. The experiment provided data to compare the mixture preparation in a hot and cold environment of pre-chamber and main combustion chamber. The experiment also gives an indication regarding the possible use of a pre-chamber sensor in a motored engine at higher boost pressures and fuel mass flows, operation points that would overheat the sensor in a fired engine. The work also includes the analysis of the fuel delivery into the pre-chamber of a direct and indirect injection engine. Furthermore, pressure and temperature measurement within the pre-chamber provides information about the critical sensor environment and helps to understand the gas exchange between the two volumes.