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The process of engine mapping in the automotive industry identifies steady-state engine responses by running an engine at a given operating point (speed and load) until its output has settled. While the time simulating this process with a computational model for one set of parameters is relatively short, the cumulative time to map all possible combinations becomes computationally inefficient. This work presents an alternative method for mapping out the steady-state response of an engine in simulation by applying bifurcation theory. The bifurcation approach used in this work allows the engine’s steady-state response to be traced through the model’s state-parameter space under the simultaneous variation of one or more model parameters. To demonstrate this approach, a bifurcation analysis of a simplified nonlinear engine model is presented.

The application of state-of-art thermoelectric generator (TEG) in automotive engine has potential to reduce more than 2% fuel consumption and hence the CO2 emissions. This figure is expected to be increased to 5%~10% in the near future when new thermoelectric material with higher properties is fabricated. However, in order to maximize the TEG output power, there are a few issues need to be considered in the design stage such as the number of modules, the connection of modules, the geometry of the thermoelectric module, the DC-DC converter circuit, the geometry of the heat exchanger especially the hot side heat exchanger etc. These issues can only be investigated via a proper TEG model. The authors introduced four ways of TEG modelling which in the increasing complexity order are MATLB function based model, MATLAB Simscape based Simulink model, GT-power TEG model and CFD STAR-CCM+ model. Both Simscape model and GT-Power model have intrinsic dynamic model performance.

Wet Clutches are used in automotive powertrains to enable compact designs and efficient gear shifting. During the slip phase of engagement, significant flash temperatures arise at the friction disc to separator interface because of dissipative frictional losses. An important aspect of the design process is to ensure the interface temperature does not exceed the material temperature threshold at which accelerated wear behavior and/or thermal degradation occurs. During the early stages of a design process, it is advantageous to evaluate numerous system and component design iterations exposed to plethora of possible drive cycles. A simulation tool is needed which can determine the critical operational conditions the system must survive for performance and durability to be assured. This paper describes a time-efficient multiphysics model developed to predict clutch disc temperatures with a runtime in the order of minutes.

Models of hybrid powertrains are used to establish the best combination of conventional engine power and electric motor power for the current driving situation. The model is characteristic for having two control inputs and one output constraint: the total torque should be equal to the torque requested by the driver. To eliminate the constraint, several alternative formulations are used, considering engine power or motor power or even the ratio between them as a single control input. From this input and the constraint, both power levels can be deduced. There are different popular choices for this one control input. This paper presents a novel model based on an input linearizing transformation. It is demonstrably superior to alternative model forms, in that the core dynamics of the model (battery state of energy) are linear, and the non-linearities of the model are pushed into the inputs and outputs in a Wiener/Hammerstein form.

In contrast to the well-established “standard” log-law wall function, the analytical wall function (AWF) as an advanced modelling approach has not been extensively used in the industrial computational fluid dynamics (CFD) applications. As the model was originally developed aiming at computations on relatively coarse meshes, potential stability issues may arise due to the pressure-gradient sensitivity if employing locally inappropriate mesh layers, typically associated with the complex geometry details. This work evaluates performance of the thermal AWF, as proposed by Suga [4], in conjunction with the main flow field computed employing the k-ζ-f turbulence model and the hybrid wall treatment (denoted as AWF-e) within the Reynolds-averaged Navier-Stokes (RANS) framework.

Automobile manufacturers and suppliers are under pressure to develop more efficient thermal management systems as fuel consumption and emission regulations become stricter and buyers demand greater comfort and safety. Additionally, engines must be very efficient and windows must deice and defog quickly. These requirements are often in conflict. Moreover, package styling and cost constraints severely limit the design of coolant and air conditioning systems. Simulation-based design and virtual prototyping can ensure greater product performance and quality at reduced development time and cost. The representation of the vehicle thermal management needs a scalable approach with 0-D, 1-D, and 3-D fluid dynamics, multi-body dynamics, 3-D structural analysis, and control unit simulation capabilities. Different combinations and complexities of the simulation tools are required for various phases of the product development process.

The objective of this study to introduce the newly developed Discrete Channel Method (DCM) as a fast and efficient method for the prediction of the 3d and transient behavior of honeycomb-type catalytic converters in automotive applications. The approach is based on the assumption that the regions between the channels are treated as a reactor with a homogeneously distributed heat source due to chemical conversion. Therefore, each radial direction can be described by a center, a boundary and only a few intermediate channels between them. The discrete channels are described by transient, 1d conservation equations that characterize the behavior of channels at different radial positions. The heat entering and leaving each discrete channel is evaluated by the gradients of the temperature field in conjunction with the heat conductivity of the substrate. The approach is validated by experimental data and serves as a module in the thermodynamic and engine analysis design tool BOOST.

Energy management of battery electric vehicle (BEV) is a very important and complex multi-system optimisation problem. The thermal energy management of a BEV plays a crucial role in consistent efficiency and performance of vehicle in all weather conditions. But in order to manage the thermal management, it requires a significant number of temperature sensors throughout the car including high voltage batteries, thus increasing the cost, complexity and weight of the car. Virtual sensors can replace physical sensors with a data-driven, physical relation-driven or machine learning-based prediction approach. This paper presents a framework for the development of a neural network virtual sensor using a thermal system hardware-in-the-loop test rig as the target system. The various neural network topologies, including RNN, LSTM, GRU, and CNN, are evaluated to determine the most effective approach.

Hybrid technologies enable the reduction of noxious tailpipe emissions and conformance with ever-decreasing allowable homologation limits. The complexity of the hybrid powertrain technology leads to an energy management problem with multiple energy sinks and sources comprising the system resulting in a high-dimensional time dependent problem for which many solutions have been proposed. Methods that rely on accurate predictions of potential vehicle operations are demonstrably more optimal when compared to rule-based methodology [1]. In this paper, a previously proposed energy management strategy based on an offline optimization using dynamic programming is investigated. This is then coupled with an online model predictive control strategy to follow the predetermined optimal battery state of charge trajectory prescribed by the dynamic program.

Understanding and predicting in-cylinder flow structures that occur within compression-ignition engines is vital if further optimisation of combustion systems is to be achieved. To enable this prediction, fully validated computational models of the complex turbulent flow-fields generated during the intake and compression process are needed. However, generating, analysing and interpreting experimental data to achieve this validation remains a complex challenge due to the variability that occurs from cycle to cycle. The flow-velocity data gathered in this study, obtained from a single-cylinder CI engine with optical access using high-speed PIV, demonstrates that significantly different structures are generated over different cycles, resulting in the mean flow failing to adequately reflect the typical flow produced in-cylinder.

This paper summarizes the results of several investigations on in-cylinder heat transfer during high-pressure and gas exchange phases as well as heat transfer in the inlet and outlet ports for a number of different engine types (DI Diesel, SI and gaseous fueled engine). The paper contains a comparision of simulation results and experimental data derived from heat flux measurements. Numerical results were obtained from zero-, one- and three-dimensional simulation methods. Time and spatially resolved heat fluxes were measured applying the surface temperature method and special heat flux sensors. The paper also includes an assessment of different sensor types with respect to accuracy and applicability.

The limitation of global warming to less than 2 °C till the end of the century is regarded as the main challenge of our time. In order to meet COP21 objectives, a clear transition from carbon-based energy sources towards renewable and carbon-free energy carriers is mandatory. Polymer electrolyte membrane fuel cells (PEMFC) allow an energy-efficient, resource-efficient and emission-free conversion of regenerative produced hydrogen. For these reasons fuel cell technologies emerge in stationary, mobile and logistic applications with acceptable cruising ranges as well as short refueling times. In order to perform applied research in the area of PEMFC systems, a highly integrated fuel cell analysis infrastructure for systems up to 150 kW electric power was developed and established within a cooperative research project by HyCentA Research GmbH and AVL List GmbH in Graz, Austria. A novel open testing facility with hardware in the loop (HiL) capability is presented.

With the implementation of EURO VI and similar emission legislation, the industry assumed the pace and stringency of new legislation would be reduced in the future. The latest announcements of proposed and implemented legislation steps show that future legislation will be even more stringent. The currently leading announced legislation, which concerns a large number of global manufacturers, is the legislation from the United States (US) Environmental Protection Agency (EPA) and the California Air Resources Board (CARB). Both announced new legislation for CO2, Greenhouse Gas (GHG) Phase II. CARB is also planning additional Ultra Low NOx regulations. Both regulations are significant and will require a number of technologies to be used in order to achieve the challenging limits. AVL published some engine related measures to address these legislation steps.

The need to improve the engine performance and fuel consumption subject to ever more stringent emission standard spar the interest in the aspects of understanding and quantifying the thermal behavior of engine components and systems. Considering these points during the design of the vehicle thermal management system based on test would consume far too many resources. Fortunately, the simulation tools have become more prominent in the pre-prototype phase of the vehicle development process and they had reached a mature stage; where they can contribute successfully to a significant extend to meet the vehicle development targets. In this work, a methodology to model the Vehicle Thermal Management System (VTMS) in order to understand and quantify its behavior has been developed. The partial systems under consideration are: the gas circuit, the cooling circuit, the lubrication circuit and the thermal capacitance of the engine structure under the vehicle driving conditions.

Future limits on emissions for both gasoline and Diesel engines require adequate and advanced systems for the after-treatment of the exhaust gas. Computer models as a complementary tool to experimental investigations are an indispensable part to design reliable after-treatment devices such as catalytic converters and Diesel particulate filters including their influence on the power-train. Therefore, the objective of this contribution is to present an integrated 1D to 3D simulation workflow of of catalytic converters and Diesel particulate filters. The novelty of this approach is that parameters or set of parameters, obtained by a fast and efficient 1D-gas exchange and cycle simulation code for power-trains (AVL (2002a)), are readily transferable onto a 3D general purpose simulation code (AVL (2002b)). Thus, detailed aspects such as spatial distribution of temperatures or heat losses are investigated with only a single effort to estimate parameters.

Modern thermal propulsion systems (TPS) as part of hybrid powertrains are becoming increasingly complex. They have an increased number of components in comparison to traditionally powered vehicles leading to increased demand in packaging requirements. Many of the components in these systems relate to achieving efficiency gains, weight saving and pollutant reduction. This includes turbochargers and diesel or gasoline particulate filters for example and these are known to be very sensitive to inlet boundary conditions. When overcoming packaging requirements, sub-optimal flow distributions throughout the TPS can easily occur. Moreover, the individual components are often designed in isolation assuming relatively flat and artificially quiescent inlet flow conditions in comparison to those they are actually presented with. Thus, some of the efficiency benefits are lost through reduced component aerodynamic efficiency.

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.

Powertrain thermal encapsulation has the potential to improve fuel consumption and CO2 via heat retention. Heat retained within the powertrain after a period of engine-off, can increase the temperature of the next engine start hours after key-off. This in turn reduces inefficiencies associated with sub-optimal temperatures such as friction. The Ambient Temperature Correction Test was adopted in the current work which contains two World-wide harmonised Light duty Test Procedure (WLTP) cycles separated by a 9-hour soak period. A coupled 1D - 3D computational approach was used to capture heat retention characteristics and subsequent warm-up effects. A 1-D powertrain warm-up model was developed in GT-Suite to capture the thermal warm-up characteristics of the powertrain. The model included a temperature dependent friction model, the thermal-hydraulic characteristics of the cooling and lubrication circuits as well as parasitic losses associated with pumps.

The de-icing process of the windscreen is a demanding problem in car climatization. In the first stages of the development procedure of air ducts, the numerical simulation plays an important role due to economy of time and money. Unfortunately, the available numerical methods for the generation of the computational grid and the simulation of the de-icing process are very time consuming and are complicated in handling. Therefore normally the quality of the de-icing process is evaluated with simplified simulation procedures or even with measurements late in the design process and necessary modifications are again time and cost consuming. The aim of this paper is to describe new methods for the de-icing simulation that will reduce meshing and calculation time by showing accurate results.

Two identical commercial Thermo-Electric Modules (TEMs) were assembled on a plate type heat exchanger to form a Thermoelectric Generator (TEG) unit in this study. This unit was tested on the Exhaust Gas Recirculation (EGR) flow path of a test engine. The data collected from the test was used to develop and validate a steady state, zero dimensional numerical model of the TEG. Using this model and the EGR path flow conditions from a 30% torque Non-Road Transient Cycle (NRTC) engine test, an optimization of the number of TEM units in this TEG device was conducted. The reduction in fuel consumption during the transient test cycle was estimated based on the engine instantaneous Brake Specific Fuel Consumption (BSFC). The perfect conversion of TEG recovered electrical energy to engine shaft mechanical energy was assumed. Simulations were performed for a single TEG unit (i.e. 2 TEMs) to up to 50 TEG units (i.e. 100 TEMs).