Search Results

Beside the automotive industry, where 2-cylinder inline engines are catching attention again, twin-cylinder configurations are quite usual in the small engine world. From stationary engines and range-extender use to small motorcycles up to big cruisers and K-Cars this engine architecture is used in many types of applications. Because of very good overall packaging, performance characteristics and not least the possibility of parts-commonality with 4-cylinder engines nearly every motorcycle manufacturer provides an inline twin in its model range. Especially for motorcycle applications where generally the engine is a rigid member of the frame and vibrations can be transferred directly to the rider an appropriate balancing system is required.

Car manufacturers put large efforts into reducing wind noise to improve the comfort level of their cars. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof designs are tested to meet low-frequency buffeting (also known as boom) targets and broadband noise targets for the fully open sunroof with deflector and for the sunroof in vent position. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process.

In spark-ignition engines, fluctuations of the in-cylinder pressure trace and the apparent rate of heat release are usually observed from one cycle to another. These Cycle-to-Cycle Variations (CCV) are affected by the early flame development and the subsequent flame front propagation. The CCV are responsible for engine performance (e.g. fuel consumption) and the knock behavior. The occurrence of the phenomena is unpredictable and the stochastic nature offers challenges in the optimization of engine control strategies. In the present work, CCV are analyzed in terms of their impact on the engine knock behavior and the related efficiency. Target is to estimate the possible fuel consumption savings in steady-state operation and in the drivecycle, when CCV are reduced. Since CCV are immanent on real engines, such a study can only be done by means of simulation.

The use of state of the art simulation tools for effective front-loading of the calibration process is essential to support the additional efforts required by the new Real Driving Emission (RDE) legislation. The process needs a critical model validation where the correlation in dynamic conditions is used as a preliminary insight into the bounds of the representation domain of engine mean values. This paper focuses on the methodologies for correlating dynamic simulations with emissions data measured during dynamic vehicle operation (fundamental engine parameters and gaseous emissions) obtained using dedicated instrumentation on a diesel vehicle, with a particular attention for oxides of nitrogen NOx specie. This correlation is performed using simulated tests run within AVL’s mean value engine and engine aftertreatment (EAS) model MoBEO (Model Based Engine Optimization).

In a real-world environment, a vehicle on the road is subjected to a range of flow yaw angles, the most severe of which can impact handling and stability. A fully coupled, six degrees-of-freedom CFD and vehicle handling simulation has modelled the complete closed loop system. Varying flow yaw angles are introduced via time dependent boundary conditions and aerodynamic loads predicted, whilst a handling model running simultaneously calculates the resulting vehicle response. Updates to the vehicle position and orientation within the CFD simulation are achieved using the overset grid method. Using this approach, a crosswind simulation that follows the parameters of ISO 12021:2010 (Sensitivity to lateral wind - Open-loop test method using wind generator input), was performed using the fastback variant of the DrivAer model. Fully coupled aerodynamic and vehicle response was compared to that obtained using the simplified quasi-steady and unsteady, one way coupled method.

Complexity of electronics and embedded software systems in automobiles has been increasing over the years. This necessitates the need for an effective and exhaustive development and validation process in order to deliver fault free vehicles at reduced time to market. Model-based Product Engineering (MBPE) is a new process for development and validation of embedded control software. The process is generic and defines the engineering activities to plan and assess the progress and quality of the software developed for automotive applications. The MBPE process is comprised of six levels (one design level and five verification and validation levels) ranging from the vehicle requirements phase to the start of production. The process describes the work products to be delivered during the course of product development and also aligns the delivery plan to overall vehicle development milestones.

In the present work, a scalable simulation methodology is presented that enables the assessment of the impact of SI-engine cycle-to-cycle combustion variations on fuel consumption and hence CO2 emissions on three different levels of modeling depth: in-cylinder, steady-state engine and transient engine and vehicle simulation. On the detailed engine combustion chamber level, a 3D-CFD approach is used to study the impact of the turbulent in-cylinder flow on the cycle-resolved flame propagation characteristics. On engine level, cycle-to-cycle combustion variations are assessed regarding their impact on indicated mean effective pressure, aiming at estimating the possible fuel consumption savings when cyclic variations are minimized. Finally, on the vehicle system level, a combined real-time engine approach with crank-angle resolved cylinder is used to assess the potential fuel consumption savings for different vehicle drivecycle conditions.

In order to meet current and future emission and CO2 targets, an efficient vehicle thermal management system is one of the key factors in conventional as well as in electrified powertrains. Global vehicle simulation is already a well-established tool to support the vehicle development process. In contrast to conventional vehicles, electrified powertrains offer an additional challenge to the thermal conditioning: the durability of E-components is not only influenced by temperature peaks but also by the duration and amplitude of temperature swings as well as temperature gradients within the components during their lifetime. Keeping all components always at the preferred lowest temperature level to avoid ageing under any conditions (driving, parking, etc.) will result in very high energy consumption which is in contradiction to the efficiency targets.

Hardware-in-the-loop (HIL) simulations have long been used to test electronic control units (ECUs) and software in car manufacturers. It provides an effective platform to the rapid development process of the ECU control algorithms and accommodates the added complexity of the plant under control. Accurate Model based HIL simulation (AMHIL) is considered as a most efficient and cost effective way for exploration of new designs and development of new products, particularly in calibration and parameterization of vehicle stability controllers. The work presented in the paper is to develop a mathematical model of a windscreen wiper system for the purpose of conducting HIL vehicle test and eventually to replace the real component with the model for cost cutting and improved test efficiency. The model is developed based on the electro-mechanical engineering principles.

The advent of 3D displays offers Human-Machine Interface (HMI) designers and engineers new opportunities to shape the user's experience of information within the vehicle. However, the application of 3D displays to the in-vehicle environment introduces a number of new parameters that must be carefully considered in order to optimise the user experience. In addition, there is potential for 3D displays to increase driver inattention, either through diverting the driver's attention away from the road or by increasing the time taken to assimilate information. Manufacturers must therefore take great care in establishing the ‘do’s and ‘don’t's of 3D interface design for the automotive context, providing a sound basis upon which HMI designers can innovate. This paper describes the approach and findings of a three-part investigation into the use of 3D displays in the instrument cluster of a road car, the overall aim of which was to define the boundaries of the 3D HMI design space.

Many electric (EV) and hybrid-electric (HEV) vehicles are designed to operate using only electric propulsion at low road speeds. This has resulted in significantly reduced vehicle noise levels in urban situations. Although this may be viewed by many as a benefit, a risk to safety exists for those who rely on the engine noise to help detect the presence, location and behaviour of a vehicle in their vicinity. In recognition of this, legislation is being introduced globally which will require automotive manufacturers to implement external warning sound systems. A key challenge for premium vehicle manufacturers is the development of a suitable warning sound signature which also conveys the appropriate brand aspirations for the product. A further major difficulty exists when trying to robustly evaluate potential exterior sounds by running large-scale trials in the real world.

This paper presents the development and implementation of an Analytical Target Cascading (ATC) Multi-disciplinary Design Optimisation (MDO) framework for the steady state engine calibration optimisation problem. The case is made that the ATC offers a convenient framework for the engine calibration optimisation problem based on steady state engine test data collected at specified engine speed / load points, which is naturally structured on 2 hierarchical levels: the ‘Global’ level, associated with performance over a drive cycle, and ‘Local’ level, relating to engine operation at each speed / load point. The case study of a diesel engine was considered to study the application of the ATC framework to a calibration optimisation problem. The paper describes the analysis and mathematical formulation of the diesel engine calibration optimisation as an ATC framework, and its Matlab implementation with gradient based and evolutionary optimisation algorithms.

Today, OEMs are challenged with an increasing number of powertrain variants and complexity of controls software. They are facing internal pressure to provide mature and refined calibrations earlier in the development process. Until now, it was difficult to respond to these requests as the drivability's calibration tasks are mostly done in vehicles. This paper describes a new methodology designed to answer these challenges by performing automated shift quality calibration prior to the availability of vehicles. This procedure is using a powertrain dynamometer coupled with a real-time vehicle dynamics model. By using a Power Train Test Bed (PTTB), a physical vehicle is not required. As soon as the vehicle dynamics model and its parameters have been defined, it can be simulated on the PTTB and drivability calibrations can be developed. A complete powertrain is coupled with low inertia and highly dynamic dynamometers.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

Due to increasing complexity of engine electronic systems, there is a demand to handle the often more than 10,000 calibration data automatically. Establishing optimized start of injection and EGR tables of a TC DI Diesel engine by conventional methods takes about two weeks of intensive calibration work. By automatic map calibration, this task can be handled in less than 20 hours automatically, with no staff required during optimization. The benefits of automatic calibration therefore are reduced costs and faster response to any changes in parameters, even with complex multidimensional engine calibration problems. The paper describes the optimization method as well as the experimental work on the test stand that produces the results.

Approaching engineering limits for the thermal design of battery modules requires virtual prototyping and appropriate models with respect to physical depth and computational effort. A multi-scale and multi-domain model describes the electrochemical behavior of a single battery unit cell in 1D+1D at the level of intra-cell phenomena, and it applies a 3D thermal model at module level. Both models are connected within a common vehicle simulation platform. The models are discussed with special emphasis on battery degradation such as solid electrolyte interphase layer formation, decomposition and lithium plating. The performance of the electrochemical model is assessed by discharge cycles and repeated charge/discharge simulations. The thermal module model is compared to CFD reference data and studied with respect to its grid sensitivity.

Calibrating a vehicle’s powertrain for dynamic operation needs to focus on efforts to mitigate the risks of thermal overload which may arise in the stator or rotor components of an e-motor. Risks also may arise for expected NVH or durability targets, with torque and torque “oscillations” acting as primary sources for the vehicles’ NVH behavior. Both topics, temperature measurement of stator and rotor as well as dynamic torque measurements of the powertrain’s drive shaft are addressed with examples demonstrating the sensors applications in normal test bed and vehicle configurations.

The automotive industry is racing to introduce some degree of hybridization into their product ranges. Since the term “hybrid vehicle” can cover a wide range of differing technologies and drivetrain topologies, this has led to a large amount of vehicles that call themselves “hybrid”. This poses an interesting challenge for marketers to differentiate these vehicles from the incumbents. However, it is not just the marketers who are faced with challenges, the developers of such hybrid drivetrains are faced with a rise in technical complexity due to the wide range of operating modes hybridization introduces. As propulsive torque is being generated in more than one place in a hybrid vehicle, the transitions from conventional drive to electrically supported drive bring with them complex aspects of multi-dimensional system control. The challenge is to be able to implement hybrid technology in an existing drivetrain, while adapting the existing components as required.

The automotive industry is racing to introduce some degree of hybridization into their product ranges. Since the term "hybrid vehicle" can cover a wide range of differing technologies and drivetrain topologies, this has led to a plethora of vehicles that call them "hybrid." This poses an interesting challenge for marketers to differentiate these vehicles from the incumbents. However, it is not just the marketers who are faced with challenges, the developers of such hybrid drivetrains are faced with a rise in technical complexity due to the wide range of operating modes hybridization introduces. As propulsive torque is being generated in more than one place in a hybrid vehicle, the transitions from conventional drive to electrically supported drive bring with them complex aspects of multi-dimensional system control. The challenge is to be able to implement hybrid technology in an existing drivetrain, while adapting the existing components as required.

When employing in-car active sound generation (ASG) and active noise cancellation (ANC), the accurate knowledge of the vehicle interior sound pressure distribution in magnitude as well as phase is paramount. Revisiting the ANC concept, relevant boundary conditions in spatial sound fields will be addressed. Moreover, within this study the controllability and observability requirements in case of ASG and ANC were examined in detail. This investigation focuses on sound pressure measurements using a 24 channel microphone array at different heights near the head of the driver. A shaker at the firewall and four loudspeakers of an ordinary in-car sound system have been investigated in order to compare their sound fields. Measurements have been done for different numbers of passengers, with and without a dummy head and real person on the driver seat. Transfer functions have been determined with a log-swept sine technique.