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Advanced powertrains for modern vehicles require the optimization of conventional combustion engines in combination with tailored electrification and vehicle connectivity strategies. The resulting systems and their control devices feature many degrees of freedom with a large number of available adjustment parameters. This obviously presents major challenges to the development of the corresponding powertrain control logics. Hence, the identification of an optimal system calibration is a non-trivial task. To address this situation, physics-based control approaches are evolving and successively replacing conventional map-based control strategies in order to handle more complex powertrain topologies. Physics-based control approaches enable a significant reduction in calibration effort, and also improve the control robustness.

Modern vehicles become increasingly software intensive. Software development therefore is critical to the success of the manufacturer to develop state of the art technology. Standards like ISO 26262 recommend requirement-based verification and test cases that are derived from requirements analysis. Agile development uses continuous integration tests which rely on test automation and evaluation. All these drove the development of a new model-based software verification environment. Various aspects had to be taken into account: the test case specification needs to be easily comprehensible and flexible in order to allow testing of different functional variants. The test environment should support different use cases like open-loop or closed-loop testing and has to provide corresponding evaluation methods for continuously changing as well as for discrete signals.

Today, automated vehicles mostly rely on ego vehicle sensors such as cameras, radar or LiDAR sensors that are limited in their sensing capability and range. Vehicle-to-everything (V2X) communication has the potential to appropriately complement these sensors and even allow for a cooperative, proactive interaction of vehicles. As such, V2X communication might play a vital role on the way to smart and efficient traffic solutions. In the public funded research project UK Autodrive, we are currently investigating and experimentally evaluating V2X-based applications based on dedicated short range communication (DSRC). Moreover, the novel application intersection priority management (IPM) is part of the research project. IPM aims at automating intersections in such a way that vehicles can pass safely and even more efficiently without the use of traffic lights or signs.

This paper introduces different modeling approaches of crankshafts, compares the refinement levels and discusses the difference between the results of the crankshaft durability calculation methodologies. A V6 crankshaft is considered for the comparison of the refinement levels depending on the deviation between the signals such as main bearing forces and deflection angle. Although a good correlation is observed between the results in low speed range, the deviation is evident through the mid to high speed ranges. The deviation amplitude differs depending on the signal being observed and model being used. An inline 4 crankshaft is considered for the comparison of the durability results. The analysis results show that the durability potential is underestimated with a classical crankshaft calculation approach which leads to a limitation of maximum speed of 5500 rpm.

Within a public founded project test cell investigations were undertaken to identify parameters which predominantly influence the development of critical deposits in injection nozzles. A medium-duty diesel engine was operated in two different coking cycles with a zinc-free lubricant. One of the cycles is dominated by rated power, while the second includes a wide area of the operation range. During the experiments the temperatures at the nozzle tip, the geometries of the nozzle orifice and fuel properties were varied. For a detailed analysis of the deposits methods of electron microscopy were deployed. In the course of the project optical access to all areas in the nozzle was achieved. The experiments were evaluated by means of the monitoring of power output and fuel flow at rated power. The usage of a SEM (scanning electron microscope) and a TEM (transmission electron microscope) revealed images of the deposits with a magnification of up to 160 000.

In order to reduce engine out CO2 emissions, it is a main subject to find new alternative fuels from renewable sources. For identifying the specification of an optimized fuel for engine combustion, it is essential to understand the details of combustion and pollutant formation. For obtaining a better understanding of the flame behavior, dynamic structure large eddy simulations are a method of choice. In the investigation presented in this paper, an n-heptane spray flame is simulated under engine relevant conditions starting at a pressure of 50 bar and a temperature of 800 K. Measurements are conducted at a high-pressure vessel with the same conditions. Liquid penetration length is measured with Mie-Scatterlight, gaseous penetration length with Shadowgraphy and lift-off length as well as ignition delay with OH*-Radiation. In addition to these global high-speed measurement techniques, detailed spectroscopic laser measurements are conducted at the n-heptane flame.

1. The present work introduces an approach for the analysis of the noise propagation behavior of mechatronic brake systems in modern passenger vehicles. While on the one hand, the number of features realized through the mechatronic brake system is strongly increasing; on the other hand, a continuous reduction of the overall vehicle interior noise level can be observed. This leads to an increase of interfering noise phenomena in the vehicle interior that customers might perceive as insufficient product quality. Therefore, noise elimination always plays an important role in vehicle development. The mechatronic brake system induces interfering noise that is transferred into the vehicle interior, differing from vehicle to vehicle and maneuver to maneuver. Supposedly, a wide frequency range, numerous components, and various branched transfer paths in the physical domains of airborne, structure-borne, and fluid-borne sound are involved in the noise propagation.

As the market for electric vehicles grows, so does the demand for appropriate charging infrastructure. The availability of sufficient charging points is essential to increase public acceptance of electric vehicles and to avoid the so-called “charging anxiety”. However, the charging stations currently installed may not be able to meet the full charging demand, especially in areas where there is a general lack of grid infrastructure, or where the fluctuating nature of charging demand requires flexible, high-power charging solutions that do not require expensive grid extensions. In such cases, the use of mobile charging stations provides a good opportunity to complement the existing charging network. This paper presents a prototype of a mobile charging solution that is being developed as part of an ongoing research project, and discusses different use cases.

The most challenging part of the engine combustion development is the reduction of pollutants (e.g. CO, THC, NOx, soot, etc.) and CO2 emissions. In order to achieve this goal, new combustion techniques are required, which enable a clean and efficient combustion. For compression ignition engines, combustion rate shaping, which manipulates the injected fuel mass to control the in-cylinder pressure trace and the combustion rate itself, turned out to be a promising opportunity. One possibility to enable this technology is the usage of specially developed rate shaping injectors, which can control the injection rate continuously. A feasible solution with series injectors is the usage of multiple injections to control the injection rate and, therefore, the combustion rate. For the control of the combustion profile, a detailed injector model is required for predicting the amount of injected fuel. Simplified 0D models can easily predict single injection rates with low deviation.

The droplet velocity is an important parameter for breakup, evaporation, and combustion of Diesel sprays, but it is very difficult to measure it by widely used laser diagnostic techniques like PDA, PIV and LCV under realistic high-pressure and high-temperature conditions. This is basically caused by laser beam steering and multiple scattering of light due to very high droplet densities, in particular close to the nozzle. It was demonstrated recently, that these problems can be greatly reduced by the laser flow tagging (LFT) technique. For this purpose, the model fuel is doped with a phosphorescent tracer. A number of droplet groups within the spray are tagged by illuminating them with focused beams of a pulsed laser, and their velocities are measured by recording the phosphorescence twice after each laser pulse using a double-frame ICCD.

Hardware-in-the-Loop is a common and established testing method for automotive developments in order to study interactions between different vehicle components during early development phases. Hardware-in-the-Loop setups have successfully been utilized within several development programs for conventional and electrified powertrains already. However, there is a particular shortage of studies focusing on the development of inverter controls utilizing Hardware-in-the-Loop tests. This contribution shall provide a first step toward closing this gap. In this article, inverter controls with different pulse width modulations for varying modulation index are studied at a Hardware-in-the-Loop setup. Thereto, the inverter control for an interior permanent magnet synchronous machine is developed utilizing space vector pulse width modulation with overmodulation.

The efficient operation of powertrain test benches in research and development is strongly influenced by the state of “health” of the functional test object. Hence, the use of Early Damage Detection Systems (EDDS) with Unit Under Test (UUT) monitoring is becoming increasingly popular. An EDDS should primarily avoid total loss of the test object and ensure that damaged parts are not completely destroyed, and can still be inspected. Therefore, any abnormality from the standard test object behavior, such as an exceeding of predefined limits, must be recognized at an early testing time, and must lead to a shutdown of the test bench operation. With sensors mounted on the test object, it is possible to isolate the damage cause in the event of its detection. Advanced EDDS configurations also optimize the predefined limits by learning new shutdown values according to the test object behavior within a very short time.

In Common-Rail DI Diesel Engines, multiple injection strategies are considered as one of the methodologies to achieve optimum performance and emission reduction. However, multiple injections open a whole new horizon of parameters which affect the combustion process. These parameters include the number of injection events, the duration between the starts of each injection event, the splitting of the total fuel mass on the different injection events, etc. In the present work, the influence of the number of injection events and the influence of the duration between the starts of each injection event on emission levels are investigated. Combustion and pollutant formation were experimentally investigated in a Common-Rail DI Diesel engine. The engine was operated at conventional part-load conditions with 2000 rpm, no external EGR, and an injected fuel mass of 15 mg/cycle.

Electrification is a key enabler to reduce emissions levels and noise in commercial vehicles. With electrification, Batteries are being used in commercial hybrid vehicles like city buses and trucks for kinetic energy recovery, boosting and electric driving. A battery management system monitors and controls multiple components of a battery system like cells, relays, sensors, actuators and high voltage loads to optimize the performance of a battery system. This paper deals with the development of modular control architecture for battery management systems in commercial vehicles. The key technical challenges for software development in commercial vehicles are growing complexity, rising number of functional requirements, safety, variant diversity, software quality requirements and reduced development costs. Software architecture is critical to handle some of these challenges early in the development process.

In order to reduce development cost and time, frontloading is an established methodology for automotive development programs. With this approach, particular development tasks are shifted to earlier program phases. One prerequisite for this approach is the application of Hardware-in-the-Loop test setups. Hardware-in-the-Loop methodologies have already successfully been applied to conventional as well as electrified powertrains considering various driving scenarios. Regarding driving performance and energy demand, electrified powertrains are highly dependent on the dc-link voltage. However, there is a particular shortage of studies focusing on the verification of variable dc-link voltage controls by Hardware-in-the-Loop setups. This article is intended to be a first step towards closing this gap. Thereto, a Hardware-in-the-Loop setup of a battery electric vehicle is developed.

The use of state-of-the-art model-based calibration tools generate only limited benefits for seamless validation in powertrain calibration due to the often neglected system-level simulation of a closed-loop vehicle environment. This study presents a Hardware-in-the-Loop (HiL)-based virtual calibration approach to establish an accurate virtual calibration platform using physical plant models. It is based on a customisable real-time HiL simulation environment. The use of physical models to predict the behaviour of a complete powertrain makes the HiL test bench particularly suited for Engine Control Unit (ECU) calibration. With the virtual test rig approach, the calibration for the critical extended driving and ambient conditions of the new Real Driving Emissions (RDE) requirements can efficiently be optimised. This technique offers a clear advantage in terms of reducing calibration time and costs.

In-use compliance under LEV III emission standards, GHG, and fuel economy targets beyond 2025 poses a great opportunity for all ICE-based propulsion systems, especially for light-duty diesel powertrain and aftertreatment enhancement. Though diesel powertrains feature excellent fuel-efficiency, robust and complete emissions controls covering any possible operational profiles and duty cycles has always been a challenge. Significant dependency on aftertreatment calibration and configuration has become a norm. With the onset of hybridization and downsizing, small steps of improvement in system stability have shown a promising avenue for enhancing fuel economy while continuously improving emissions robustness. In this paper, a study of current key technologies and associated emissions robustness will be discussed followed by engine and aftertreatment performance target derivations for LEV III compliant powertrains.

Auto transformer rectifier units (ATRUs) are commonly used in aircraft applications such as electric actuation for harmonic mitigation due to their high reliability and relative low cost. However, those components and the magnetic filter components associated to it are the major contributors to the overall size and weight of the system. Optimization of the magnetic components is essential in order to minimize weight and size, which are major market drivers in aerospace industry today. This requires knowledge of the harmonic content of the current. This can be obtained by simulation, but the process is slow. In order to enable fast and efficient design space exploration of optimal solutions, an algebraic calculation process is proposed in this paper for multi-pulse ATRUs (e.g. 12-pulse and 18-pulse rectifiers), starting from existing solution proposed for 6 pulse rectifier in the literature.

With the increasing application of the lithium ion battery technology in automotive industry, development processes and validation methods for the battery management system (BMS) have drawn more and more attentions. One fundamental function of the BMS is to continuously estimate the battery’s state-of-charge (SOC) and state-of-health (SOH) to guarantee a safe and efficient operation of the battery system. For SOC as well as SOH estimations of a BMS, there are certain non-ideal situations in a real vehicle environment such as measurement inaccuracies, variation of cell characteristics over time, etc. which will influence the outcome of battery state estimation in a negative way. Quantifying such influence factors demands extensive measurements. Therefore, we have developed a model-in-the-loop (MIL) environment which is able to simulate the operating conditions that a BMS will encounter in a vehicle.

This paper will present a multi-domain (electrical and thermal) model of a three phase voltage source converter and its implementation in Modelica language. An averaged model is utilised for the electrical domain, and a power balance method is used for linking the DC and AC sides. The thermal domain focuses in deriving the converter losses by deriving the analytical equations of the space vector modulation to derive a function for the duty cycle of each converter leg. With this, the conduction and switching losses are calculated for the individual switches and diodes, without having to model their actual switching behaviour. The model is very fast to simulate, as no switching events are needed, and allows obtaining the simulation of the electrical and thermal behaviour in the same simulation package..