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Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

In the last couple of decades, countries have enacted new laws concerning environmental pollution caused by heavy-duty commercial and passenger vehicles. This is done mainly in an effort to reduce smog and health impacts caused by the different pollutions. One of the legislated pollutions, among a wide range of regulated pollutions, is nitrogen oxides (commonly abbreviated as NOx). The SCR (Selective Catalytic Reduction) was introduced in the automotive industry to reduce NOx emissions leaving the vehicle. The basic idea is to inject a urea solution (AdBlue™) in the exhaust gas before the gas enters the catalyst. The optimal working temperature for the catalyst is somewhere in the range of 300 to 400 °C. For the reactions to occur without a catalyst, the gas temperature has to be at least 800 °C. These temperatures only occur in the engine cylinder itself, during and after the combustion.

An afterburner-assisted turbocharged single-cylinder 425 cc two-stroke SI-engine is described in this simulation study. This engine is intended as a Backup Range Extender (REX) application for heavy-duty battery electric vehicles (BEV) when external electric charging is unavailable. The 425 cc engine is an upscaled version of a 125 cc port-injected engine [26] which demonstrated that the selected technology could provide a specific power level of 400 kW/L and the desired 150 kW in a heavy duty BEV application. The 425 cc single cylinder two-stroke engine is an existing engine as one half of a 850 cc snowmobile engine. This simulation study includes upscaling of the swept volume, impact on engine speed and gas exchange properties. In the same way as for the 125cc engine [26], the exhaust gases reaches the turbine through a tuned exhaust pipe and an afterburner or oxidation catalyst.

Diffusive combustion of direct injected ethanol is investigated in a heavy-duty single cylinder engine for a broad range of operating conditions. Ethanol has a high potential as fossil fuel alternative, as it provides a better carbon footprint and has more sustainable production pathways. The introduction of ethanol as fuel for heavy-duty compression-ignition engines can contribute to decarbonize the transport sector within a short time frame. Given the resistance to autoignition of ethanol, the engine is equipped with two injectors mounted in the same combustion chamber, allowing the simultaneous and independent actuation of the main injection of pure ethanol and a pilot injection of diesel as an ignition source. The influence of the dual-fuel injection strategy on ethanol ignition, combustion characteristics, engine performance and NOx emissions is evaluated by varying the start of injection of both fuels and the ethanol-diesel ratio.

Renewable fuels from different feedstocks can enable sustainable transport solutions with significant reduction in greenhouse gas emissions compared to conventional petroleum-derived fuels. Nevertheless, the use of biofuels in diesel engines will still require similar exhaust gas cleaning systems as for conventional diesel. Hence, the use of diesel particulate filters (DPF) will persist as a much needed part of the vehicle’s aftertreatment system. Combustion of renewable fuels can potentially yield soot and ash with different properties as well as larger amounts of ash compared to conventional fossil fuels. The faster ash build-up and altered ash deposition pattern lead to an increase in pressure drop over the DPF, increase the fuel consumption and call for premature DPF maintenance or replacement. Prolonging the maintenance interval of the DPF for heavy-duty trucks, having a demand for high up-time, is highly desirable.

Advanced driver assistance systems (ADAS) are becoming increasingly important for today's commercial vehicles. It is therefore crucial that different ADAS functionalities interact seamlessly with existing electronic control unit (ECU) networks. For example, autonomous emergency braking (AEB) systems directly influence the brake ECU and engine control. It has already become impossible to reliably validate this growing interconnectedness of control interventions in vehicle behavior with prototype vehicles alone. The relevant tests must be brought into the lab at an earlier development stage to evaluate ECU interaction automatically. This paper presents an approach for using hardware-in-the-loop (HIL) simulation to validate ECU networks for extremely diverse ADAS scenarios, while taking into account real sensor data. In a laboratory environment, the sensor systems based on radars, cameras, and maps are stimulated realistically with a combination of simulation and animation.

In the aerospace industry, methods for virtual testing cover an increasing range of test executions carried out during the development and test process of avionics systems. Over the last years, most companies have focused on questions regarding the evaluation and implementation of methods for virtual testing. However, it has become more and more important to seamlessly integrate virtual testing into the overall development process. For instance, a company’s test strategy might stipulate a combination of different methods, such as SIL and HIL simulation, in order to benefit from the advantages of both in the same test process. In this case, efforts concentrate on the optimization of the overall process, from test specification to test execution, as well as the test result evaluation and its alignment with methods for virtual testing.

Biofuel can enable a sustainable transport solution and lower greenhouse gas emissions compared to standard fuels. This study focuses on biodiesel, implemented in the easiest way as drop in fuel. When mixing biodiesel into diesel one can run into problems with solubility causing contaminants precipitating out as insolubilities. These insolubilities, also called soft particles, can cause problems such as internal injector deposits and nozzle fouling. One way to overcome the problem of soft particles is by filtration. It is thus of great interest to be able to quantify fuel filters’ ability to intercept soft particles. The aim of this study is to test different fuel filters for heavy-duty engines and their ability to filter out synthetic soft particles. A custom-built fuel filter rig is presented, together with some of its general design requirements. For evaluation of the efficiency of the filters, fuel samples were taken before and after the filters.

Real-time simulation of truck and trailer combinations can be applied to hardware-in-the-loop (HIL) systems for developing and testing electronic control units (ECUs). The large number of configuration variations in vehicle and axle types requires the simulation model to be adjustable in a wide range. This paper presents a modular multibody approach for the vehicle dynamics simulation of single track configurations and truck-and-trailer combinations. The equations of motion are expressed by a new formula which is a combination of Jourdain's principle and the articulated body algorithm. With the proposed algorithm, a robust model is achieved that is numerically stable even at handling limits. Moreover, the presented approach is suitable for modular modeling and has been successfully implemented as a basis for various system definitions. As a result, only one simulation model is needed for a large variety of track and trailer types.

Partially Premixed Combustion (PPC) is a combustion concept which aims to provide combustion with low smoke and NOx with high thermal efficiency. Extending the ignition delay to enhance the premixing, avoiding spray-driven combustion and controlling the combustion temperature at an optimum level through use of suitable lambda and EGR levels have been recognized as key factors to achieve such a combustion. Fuels with high ignitability resistance have been proven to be a useful to extend the ignition delay. In this work pure ethanol has been used as a PPC fuel. The objective of this research was initially to investigate the required operating conditions for PPC with ethanol. Additionally, a sensitivity analysis was performed to understand how the required parameters for ethanol PPC such as lambda, EGR rate, injection pressure and inlet temperature influence the combustion in terms of controllability, stability, emissions (i.e.

In the automotive industry, the piezo-based in-cylinder pressure sensor is getting commercialized and used in production vehicles. For example, the pressure sensor offers the opportunity to design algorithms for estimation of engine emissions, such as soot and NO , during a combustion cycle. In this paper a zero-dimensional NO model for a diesel engine is implemented that will be used in real time. The model is based on the thermal NO formation and the Zeldovich mechanism using two non-geometrical zones: burned and unburned zone. The influence of EGR on combustion temperature was modeled using a well-known thermodynamic identity where specific heat at constant pressure is included. Specific heat will vary with temperature and the gas composition. The model was implemented in LabVIEW using tools specific for an FPGA (Field-Programmable Gate Array).

This paper investigates the FPGA resources for the implementation of in-cycle closed-loop combustion control algorithms. Closed-loop combustion control obtains feedback from fast in-cylinder pressure measurements for accurate and reliable information about the combustion progress, synchronized with the flywheel encoder. In-cycle combustion control requires accurate and fast computations for their real-time execution. A compromise between accuracy and computation complexity must be selected for an effective combustion control. The requirements on the signal processing (evaluation rate and digital resolution) are investigated. A common practice for the combustion supervision is to monitor the heat release rate. For its calculation, different methods for the computation of the cylinder volume and heat capacity ratio are compared. Combustion feedback requires of virtual sensors for the misfire detection, burnt fuel mass and pressure prediction.

In this article, a virtual sensor for the estimation of the injected pilot mass in-cycle is proposed. The method provides an early estimation of the pilot mass before its combustion is finished. Furthermore, the virtual sensor can also estimate pilot masses when its combustion is incomplete. The pilot mass estimation is conducted by comparing the calculated heat release from in-cylinder pressure measurements to a model of the vaporization delay, ignition delay, and the combustion dynamics. A new statistical approach is proposed for the detection of the start of vaporization and the start of combustion. The discrete estimations, obtained at the start of vaporization and the start of combustion, are optimally combined and integrated in a Kalman Filter that estimates the pilot mass during the vaporization and combustion. The virtual sensor was programmed in a field programmable gate array (FPGA), and its performance tested in a Scania D13 Diesel engine.

The application of a communication infrastructure for hybrid test systems is currently a topic in the aerospace industry, as also in other industries. One main reason is flexibility. Future laboratory tests means (LTMs) need to be easier to exchange and reuse than they are today. They may originate from different suppliers and parts of them may need to fulfill special requirements and thus be based on dedicated technologies. The desired exchangeability needs to be achieved although suppliers employ different technologies with regard to specific needs. To achieve interoperability, a standardized transport mechanism between test systems is required. Designing such a mechanism poses a challenge as there are several different types of data that have to be exchanged. Simulation data is a prominent example. It has to be handled differently than control data, for example. No one technique or technology fits perfectly for all types of data.

This paper will first introduce and classify the basic principles of architecture-driven software development and will briefly sketch the presumed development process. This background information is then used to explain extensions which enable current behavior modeling and code generation tools to operate as software component generators. The generation of AUTOSAR software components using dSPACE's production code generator TargetLink is described as an example.

Today, hardware-in-the-loop (HIL) simulation is common practice as a testing methodology for electronic control units (ECUs). An essential criterion for the efficiency of an HIL system is the availability of powerful test automation having access to all of its hardware and software components (including I/O channels, failure insertion units, bus communication controllers and diagnostic interfaces). The growing complexity of vehicle embedded systems, which are interconnected by bus systems (like CAN, LIN or FlexRay), result in hundreds or even thousands of tests that have to be done to ensure the correct system functionality. This is best achieved by automated testing. Automated testing usually is performed by executing tests on a standard PC, which is interconnected to the HIL system. However, higher demands regarding timing precision are hard to accomplish. As an example, ECU interaction has to be captured and responded to in the range of milliseconds.

Due to tougher legislation on exhaust emissions reduction and the consumer demand for more power and mobility and less fuel consumption, the functionality in today's engine management systems continues to grow. The electronic engine control units (ECUs) have to perform more control tasks using new sensors and actuators, along with the corresponding self-diagnostics (OBD, on-board diagnosis). All this leads to continuously increasing demands on automated hardware-in-the-loop (HIL) test systems. HIL technology has advanced in parallel to the ECUs, and is today an indispensable tool for developing automotive electronics. This paper therefore aims to provide a comprehensive and state-of-the-art survey of HIL test systems for engine controllers. First of all, a brief introduction to the ECU's functionality is given.

Electric drives are growing in importance in automotive applications, especially in hybrid electric vehicles (HEV) and in the vehicle dynamics area (steering systems, etc.). The challenges of real-time hardware-in-the-loop (HIL) simulation and testing of electric drives are addressed in this paper. In general, three different interface levels between the electric drive and the hardware-inthe-loop system can be distinguished: the signal level (1), the electrical level (2) and the mechanical level (3). These interface levels, as well as modeling and I/O-related aspects of electric drives and power electronics devices, are discussed in detail in the paper. Finally, different solutions based on dSPACE simulator technology are presented, for both hybrid vehicle and steering applications.

Validating control units with hardware-in-the-loop (HIL) simulators is an established method for quality enhancements in automotive software. It is primarily used for testing applications, but in view of increased networking between electronic control units, it can also be used for testing communication scenarios. The testing of electronic control unit (ECU) communication often includes only positive testing. Simple communication nodes are used for this, and communication analyzers are used for verifying communication up to the physical level. However, it is not only an ECU's positive communication behavior that has to be tested, but also its correct behavior in the event of communication errors. In HIL communication scenarios, it is not only possible to emulate the missing bus nodes (restbus simulation) with a link to real-time signals; correct ECU behavior in the event of communication errors can also be tested.

The use of Selective Catalytic Reduction (SCR) is becoming increasingly more popular as a way of reducing NOx emissions from heavy duty vehicles while maintaining competitive operating costs. In order to make efficient use of these systems, it's important to have a complete system approach when it comes to calibration of the engine and aftertreatment system. This paper presents a simplified model of a heavy duty SCR catalyst, primarily intended for use in combination with an engine-out emissions model to perform model based offline optimization of the complete system. The traditional way of modelling catalysts using a dense discretization of the catalyst channels and non-linear differential equation solvers to solve the heat and mass balance equations, requires too much computational power in this application. The presented model is also useful in other applications such as model based control.