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Society is moving towards climate neutrality where hydrogen fuelled combustion engines (H2 ICE) could be considered a main technology. These engines run on hydrogen (H2) so carbon-based emission are only present at a very low level from the lube oil. The most important pollutants NO and NO2 are caused by the exhaust aftertreatment system as well as CO2 coming from the ambient air. For standard measurement technologies these low levels of CO2 are hard to detect due to the high water content. Normal levels of CO2 are between 400-500 ppm which is very close or even below the detection limit of commonly used non-dispersive-infrared-detectors (NDIR). As well the high water content is very challenging for NOx measuring devices, like chemiluminescence detectors (CLD), where it results in higher noise and therefore a worse detection limit. Even for Fourier-transformed-infrared-spectroscopy-analysers (FT-IR) it is challenging to deal with water content over 15% without increased noise.

The production of electric vehicles (EVs) has a significant environmental impact, with up to 50 % of their lifetime greenhouse gas potential attributed to manufacturing processes. The use of sustainable materials in EV design is therefore crucial for reducing their overall carbon footprint. Wood laminates have emerged as a promising alternative due to their renewable nature. Additionally, wood-based materials offer unique damping properties that can contribute to improved Noise, Vibration, and Harshness (NVH) characteristics. In comparison to conventional materials such as aluminum, ply wood structures exhibit beneficial damping properties. The loss factor of plywood structures with a thickness below 20 mm ranges from 0.013 to 0.032. Comparable aluminum structures however exhibit only a fraction of this loss factor with a range between 0.002 and 0.005.

Today, the battery development process for automotive applications is relatively decoupled from the vehicle integration and system validation phase. Battery pack design targets are often disregarded at very early development phases even though they are thoroughly linked to the vehicle-level requirements such as performance, lifetime and cost. Here, AVL proposes a methodology guided by virtual testing techniques to frontload vehicle-level validation tasks in the earlier phase of battery pack testing. This paper focuses on the benefits of the methodology for both battery suppliers and automotive OEMs. Applications will be explained, based on a modular virtual testing toolchain, which involves the simulation platform and models as well as the generation of model parameters and test cases.

Legislative challenges, changing customer needs and the opportunities opened-up by electrification are the major driving forces in today’s automotive industry. Fuel cell vehicles offer the potential for CO2 emission free mobility, especially attractive for heavy duty long-haul range application. The development of key components of fuel cell powered vehicles, namely the fuel cell stack itself as well as the related hydrogen/air supply and thermal management sub-systems, goes hand in hand with various challenges regarding performance, lifetime and safety. The proper layout and sizing of the stack and the related fuel and air supply system components, as well as the suitable dimensioning of the cooling system, are decisive for the overall system efficiency and achievable lifetime.

As alternative to electrification or carbon free fuels such as hydrogen, CO2-neutral fuels have been researched aiming to decrease the impact of fossil energy sources on the environment. Despite the potential benefit of capturing CO2 emission after combustion for own fuel production, the so-called eFuels also benefit by using a green source of energy during their fabrication. Among all the possibilities for eFuels, alcohols, ethers (such as MTBE and ETBE) and alternative hydrocarbons have shown positive impacts regarding emission reduction and performance when compared to standard gasoline. Previously in [1] and [2], synthetic fuels and methanol blends were tested at steady state conditions in order to verify advantages and drawbacks relative to gasoline, for power-sport motorcycles.

Currently, emission regulations for the LVs using standard spark ignited ICEs considering only gaseous pollutants, just as CO, HC and NOx. Following the upcoming legislation for personal vehicles sector, the LVs might also include limits of PN and PM. Regarding fuel injection strategies, the MPFI which was previously excluded from particulate control will be incorporated into the new regulation [1]. In terms of social harm, there will be a necessity to reduce engine particulate emissions, as they are known for being carcinogenic substances [2, 3, 4]. Generally, the smaller the particulate diameter, the more critical are the damages for human health therefore, the correct determination of PN and particulate diameter is essential. Beside future challenges for reducing and controlling particulates, the reduction of fossil fuel usage is also an imminent target, being the replacement by eFuels one of the most promising alternatives.

Following the recent trend in the automotive industry, hybrid and pure electric powertrain systems are more and more preferred over conventional combustion powertrain systems due to their significant potential to reduce greenhouse-gas emissions. Although electric powertrains do not produce direct emissions during their operational time, the indirect emissions over their whole life cycle have to be taken into consideration. In this direction, the carbon footprint due to the electrification of the hand-held power tool industry needs to be examined in the preliminary design phase. In this paper, after defining the carbon footprint calculation framework, assumptions and simplifications used for the calculations, a direct comparison of the total carbon dioxide equivalent (CO2eq) emissions of three equivalent power and range powertrain systems - a combustion-driven, a hybrid-driven, and a cordless electric-driven - is presented.

To achieve global climate goals, greenhouse gas emissions must be drastically reduced. The energy and transportation sectors are responsible for about one third of the greenhouse gases emitted worldwide, and they often use internal combustion engines (ICE). One effective way to decarbonize ICEs may be to replace carbon-containing fossil fuels such as natural gas entirely, or at least partially, with hydrogen. Cost-effective development of sustainable combustion concepts for hydrogen and natural gas/hydrogen mixtures in ICEs requires the intensive use of fast and robust simulation tools for prediction. The key challenge is appropriate modeling of flame front propagation. This paper evaluates and applies different approaches to modeling laminar flame speeds from the literature. Both appropriate models and reaction kinetic calculations are considered.

Precise prediction of combustion parameters such as peak firing pressure (PFP) or crank angle of 50% burned mass fraction (MFB50) is essential for optimal engine control. These quantities are commonly determined from in-cylinder pressure sensor signals and are crucial to reach high efficiencies and low emissions. Highly accurate in-cylinder pressure sensors are only applied to test rig engines due to their high cost, limited durability and special installation conditions. Therefore, alternative approaches which employ virtual sensing based on signals from non-intrusive sensors retrieved from common knock sensors are of great interest. This paper presents a comprehensive comparison of selected approaches from literature, as well as adjusted or further developed methods to determine engine combustion parameters based on knock sensor signals. All methods are evaluated on three different engines and two different sensor positions.

The safety of BEVs in driving, charging and parking condition is essential for the success of electrification in automotive industry as well as key driver of any future development of Li-Ion HV battery. AVL has developed a unique simulation approach in which the multi-physical behavior of the single cell in thermal runaway is modelled and applied to module, pack or vehicle level. In addition and beside this cell behavior, various more physical phenomena during thermal propagation on pack level are considered and predicted by the simulation method: component melting, ignition and flammibilty of venting gas and HV failures.

In this paper, the multi-physical simulation workflow from electromagnetics to structural dynamics for a squirrel-cage induction machine is explored. In electromagnetic simulations, local forces and rotor torque are calculated for specific speed-torque operation points. In order to consider non-linearities and interaction with control system as well as transmission, time-domain simulations are carried out. For induction machines, the computational effort with full transient numerical methods like finite element analysis (FEA) is very high. A novel reduced order electro-mechanical model is presented. It still accounts for vibro-acoustically relevant harmonics due to pulse-width modulation (PWM), slotting, distributed winding and saturation effects, but is substantially faster (minutes to hours instead of days to weeks per operation point).

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.

The demand for high efficiency powertrains in automotive engineering is further increasing, with hybrid powertrains being a feasible option to cope with new legislations. So far hybridization has only played a minor role for L-category vehicles. Focusing on an exemplary high-power L-category on-road vehicle, this research aims to show a new development approach, which combines longitudinal dynamic simulation (LDS) with “Design of Experiments” (DoE) in course of hybrid electric powertrain development. Furthermore, addressing the technological aspect, this paper points out how such a vehicle can benefit from 48V-hybridization of its already existing internal combustion powertrain. A fully parametric LDS model is built in Matlab/Simulink, with exchangeable powertrain components and an adaptable hybrid operation strategy. Beforehand, characterizing decisions as to focus on 48V and on parallel hybrid architecture are made.

On the basis of small hybrid powertrain investigations in hand-held power tools for fuel consumption and emissions reduction, the prototype hybrid configuration of a small single-cylinder four-stroke internal combustion engine together with a brushless DC electric motor is built and measured on the testbench in terms of efficiency and emissions but also torque and power capabilities. The onboard energy storage system allows the combustion engine electrification for controlling the fuel amount and the combustion behavior while the electric motor placement instead of the pull-start and flywheel allows for start-stop of the system and load point shifting strategy for lower fuel consumption. The transient start-up results as well as the steady-state characterization maps of the system can set the limits on the fuel consumption reduction for such a hybrid tool compared with the baseline combustion-driven tool for given load cycle characteristics.

Virtual sensing refers to the processing of desired physical data based on measured values. Virtual sensors can be applied not only to obtain physical quantities which cannot be measured or can only be measured at an unreasonable expense but also to reduce the number of physical sensors and thus lower costs. In the field of spark ignited internal combustion engines, the virtual sensing approach may be used to predict the cylinder pressure signal (or characteristic pressure values) based on the acceleration signal of a knock sensor. This paper presents a method for obtaining the cylinder pressure signal in the high-pressure phase of an internal combustion engine based on the measured acceleration signal of a knock sensor. The approach employs a partial differential equation to represent the physical transfer function between the measured signal and the desired pressure. A procedure to fit the modeling constants is described using the example of a large gas engine.

Increasing demands regarding the efficiency and emissions of internal combustion engines will require higher peak firing pressures and increased indicated mean effective pressures in the future. Adaptation of these parameters will result in higher thermal and mechanical loads that act on core engine components. To meet the future requirements, it is essential to make changes to the design of the tribological system, which is composed of the piston, piston rings, liner and lube oil, while maintaining the robustness and reliability of the engine and its components. Modification of the tribological system requires in-depth knowledge of wear and friction. This paper presents the setup of a model of the tribological system (piston, piston rings, liner and lube oil) of a large gas engine in the commercial software AVL EXCITE™ Piston&Rings as well as its calibration and validation with data obtained from a test bed.

A transient behavior investigation of a hybrid hand-held tool is carried out on near real load conditions, through a hybrid experimental and simulative study. As this study focuses on handheld tools with a varied or transient load operation like chainsaws and brush cutters, a use of a blower tool as a test-carrier and a throttle body implementation on its blower air pipe adds a controllable braking mechanism. This allows for driving varied load cycles without the need of a testbench. Experimental investigation takes place at both start-up, shut-down and load conditions and for different drive control and commutation modes of electric motor. The controller characterization and parameter selection are done. After the load cycles are driven on the test-carrier, the characterizing data are transferred to the MATLAB and Simulink simulation model to correct and calibrate its transient behavior.

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.

In the ongoing competition of powertrain concepts the Internal Combustion Engine (ICE) will also have to demonstrate its potential for increased efficiency [1]. Variable Compression Ratio (VCR) Systems for Internal Combustion Engines (ICE) can make an important contribution to meeting stringent global fuel economy and CO2 standards. Using such technology a CO2 reduction of between 5% and 9% in the World Harmonized Light-Duty Vehicle Test Cycle (WLTC) are achievable, depending on vehicle class, load profile and power rating [2]. This paper provides a detailed description of the measurement approaches that are used during development of the AVL Dual Mode VCSTM and other VCR systems in fired operation. Results obtained from these measurements are typically used to calibrate or verify simulation models, which themselves are an integral part of the development of these systems [3].

Eliminating toxic exhaust emissions, amongst them particulate matter (PM), is one of the driving factors behind the increasing use of electrified vehicles. However, it is frequently overseen that PM arise not only from combustion, but from non-exhaust traffic related causes as well; in particular from the vehicle brakes, tires and the road surface. Furthermore, as electrified vehicles weigh more and typically exhibit higher torques at low speeds, their non-exhaust emissions tend to be higher than for comparable conventional vehicles, especially those generated by tires. Fortunately, tire related emissions are directly related to tire wear, so that limiting tire wear can reduce these emissions as well. This can be accomplished by intelligently modulating the vehicle torque profile in real time, to limit the operation in conditions of higher tire wear.