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Maintaining the current ratio between certified and the customer-observed fuel consumption even with future required levels poses a considerable challenge. Increasing the efficiency of the driveline enables certified fuel consumption down to a feasible level in the order of 80 g CO₂/km using fossil fuels. Mainly affecting off-cycle fuel consumption, energy amounts used to create good interior climate as well as energy-consuming options and features threaten to further increase. Progressing urbanization will lead to decreasing average vehicle speeds and driving distances. Highly efficient powertrains come with decreased amounts of waste energy traditionally used for interior climate conditioning, thus making necessary a change of auxiliary systems.

The automotive industry makes extensive use of virtual models to increase efficiency during the development stage. The complexity of such virtual models increases with the complexity of the process that they describe, and thus new methods for their development are constantly evaluated. Among many others, data-driven techniques and machine learning offer promising results, creating deep neural networks that map complex input-output relations. This work aims at comparing the performance of two different neural network architectures for the estimation of the engine state and emissions (flow fuel, NOx and soot). More specifically, Convolutional Neural Network (CNN) and Long-Short Term Memory (LSTM) will be evaluated in terms of performance, using different techniques to increase the model generalization. During the learning stage data from different engine cycles are fed to the neural networks.

Spray characteristics of fossil Diesel fuel, hydrotreated vegetable oil (HVO) and two oxygenated fuel blends were studied to elucidate the combustion process. The fuels were studied in an optically accessible high-pressure/high-temperature chamber under non-combusting (623 K, 4.69 MPa) and combusting (823 K, 6.04 MPa) conditions. The fuel blends contained the long-chain alcohol 2-ethylhexanol (EH), HVO and either 20 vol.% Diesel or 7 vol.% rapeseed methyl ester (RME) and were designed to have a Diesel-like cetane number (CN). Injection pressures were set to 120 MPa and 180 MPa and the gas density was held constant at 26 kg/m3. Under non-combusting conditions, shadow imaging revealed the penetration length of the liquid and vapor phase of the spray. Under combusting conditions, the lift-off length and soot volume fraction were measured by simultaneously recording time-resolved two-dimensional laser extinction, flame luminosity and OH* chemiluminescence images.

The high-pressure isobaric combustion has been proposed as the most suitable combustion mode for the double compre4ssion expansion engine (DCEE) concept. Previous experimental and simulation studies have demonstrated an improved efficiency compared to the conventional diesel combustion (CDC) engine. In the current study, isobaric combustion was achieved using a single injector with multiple injections. Since this concept involves complex phenomena such as spray to spray interactions, the computational models were extensively validated against the optical engine experiment data, to ensure high-fidelity simulations. The considered optical diagnostic techniques are Mie-scattering, fuel tracer planar laser-induced fluorescence (PLIF), and natural flame luminosity imaging. Overall, a good agreement between the numerical and experimental results was obtained.

A design method for ultra-dependable control-by-wire systems is presented here. With a top-down approach, exploiting the system's intrinsic redundancy combined with a scalable software redundancy, it is possible to meet dependability requirements cost-effectively. The method starts with the system's functions, which are broken down to the basic elements; task, sensor or actuator. A task graph shows the basic elements interrelationships. Sensor and actuator nodes form a non-redundant hardware architecture. The functional task-graph gives input when allocating software on the node architecture. Tasks are allocated to achieve low inter-node communication and transient fault tolerance using scalable software redundancy. Hardware is added to meet the dependability requirements. Finally, the method describes fault handling and bus scheduling. The proposed method has been used in two cases; a fly-by-wire aircraft and a drive-by-wire car.

Thermographic phosphors thermometry was used to measure engine valves and transparent piston temperatures in two dimensions as well point wise of a running, optically accessible, gasoline direct injection engine. The engine, fueled with isooctane, was operated in continuous and skip-fire mode at 1200 and 2000 rpm. A calibration of the phosphorescence lifetime and spectral properties against temperature allowed temperature measurements between 25 and 600°C. Results from the measurements show the potential of the technique for two-dimensional mapping of engine walls, valves and piston temperatures inside the cylinder.

The objective of this paper is to investigate whether different appearance modes of the digital human models (DHM or manikins) affect the observers when judging a working posture. A case where the manikin is manually assembling a battery in the boot with help of a lifting device is used in the experiment. 16 different pictures were created and presented for the subjects. All pictures have the same background, but include a unique posture and manikin appearance combination. Four postures and four manikin appearances were used. The subjects were asked to rank the pictures after ergonomic assessment based on posture of the manikin. Subjects taking part in the study were either manufacturing engineering managers, simulation engineers or ergonomists. Results show that the different appearance modes affect the ergonomic judgment. A more realistic looking manikin is rated higher than the very same posture visualized with a less natural appearance.

Most OEMs are shifting their strategy and way of thinking regarding ECUs. This, in combination with the electrification of vehicles and the shift towards software-based companies (car as a device), implies one of the biggest paradigm changes in automotive history. On the other hand, despite the current struggles, remarkable advances have been made in electronic technology during the past few years. These developments have opened a door to very promising enabling technology, with exterior lighting as a main target market. These circumstances seem to have created a perfect storm leading to new strategies for electronic control and driving for (front and rear) exterior lighting. We, at our company, have investigated the enabling technology, challenges, and benefits of this emerging exterior lighting approach, that we call ‘ECU-Less’.

For cost-beneficial reasons simulations with computer manikins have been increasingly used in the automotive industry for prediction of ergonomics problems before the product and work place exist in physical form. The main purpose of ergonomics simulations is to apply biomechanical models and data to assess the acceptability of the physical work load, e.g. working postures, visibility, clearance etc., which could result in requirements to change the design of the product. The aim is to improve ergonomics conditions in manual assembly and to promote a better product quality through improved assemblability (ease of assembly). Many studies have shown a clear correlation between assembly ergonomics and product quality and that poor assembly ergonomics result in impaired product quality and in decreased productivity. Nevertheless, there are remaining difficulties in achieving acceptance for changes of product and production solutions because of poor assembly ergonomics.

The transition towards battery electric vehicles (BEVs) has increased the focus of vehicle manufacturers on energy efficiency. Ensuring adequate airflow through the heat exchanger is necessary to climatize the vehicle, at the cost of an increase in the aerodynamic drag. With lower cooling airflow requirements in BEVs during driving, the front air intakes could be made smaller and thus be placed with greater freedom. This paper explores the effects on exterior aerodynamics caused by securing a constant cooling airflow through intakes at various positions across the front of the vehicle. High-fidelity simulations were performed on a variation of the open-source AeroSUV model that is more representative of a BEV configuration. To focus on the exterior aerodynamic changes, and under the assumption that the cooling requirements would remain the same for a given driving condition, a constant mass flow boundary condition was defined at the cooling airflow inlets and outlets.

The effects of nozzle geometry on diesel spray characteristics were studied in a spray chamber under evaporating conditions using three single-hole nozzles, one cylindrical and two convergent, designated N1 (outlet diameter 140 μm, k-factor 0), N2 (outlet diameter 140 μm, k-factor 2) and N3 (outlet diameter 136 μm, k-factor 2). Spray experiments were performed with each nozzle at two constant gas densities (15 and 30 kg/m3) and an ambient temperature (673 K) at which evaporation occurs, with injection pressures ranging from 800 to 1600 bar. A light absorption and scattering method using visible and UV light was implemented, and shadow images of liquid and vapor phase fuel were recorded with high-speed video cameras. The cylindrical nozzle N1 yielded larger local vapor cone angles than the convergent nozzles N2 and N3 at both gas densities, and the difference became larger as the injection pressure increased.

The automotive industry strives to develop high quality vehicles in a short period of time that satisfy the consumer needs and stand out in the competition. Full exploitation of simulation and Computer-Aided Engineering (CAE) tools can enable quick evaluation of different vehicle concepts and setups without the need of building physical prototypes. Addressing the aforementioned statements this paper presents a method for optimising the Electric Power-Assisted Steering (EPAS) ECU parameters employing solely CAE. The objective of the optimisation is to achieve a desired steering response. The developed process is tested on three specific steering metrics (friction feel, torque build-up and torque deadband) for two function parameters (basic steering torque and active return) of the EPAS. The optimisation method enabled all metrics to fall successfully within the target range.

In 1993 new European legislation regarding side-markers for passenger cars became effective. Volvo requested the TNO-Human Factors Research Institute (HFRI) to investigate the possible safety benefit of this European side-markers configuration. A test panel at TNO- HFRI was used to determine the difference in response time and detection error of drivers, confronted with slides of vehicles with and without the mentioned new vehicle side-marker configuration in several visibility conditions, crossing illumination and different vehicle approach angles. The investigation showed a significant faster vehicle recognition with less detection errors in case the approaching car was equipped with the bright amber side-markers. This improved vehicle conspicuity can be a benefit in crash avoidance, especially when the driver approaches a crossing with complex light environment and reduced visibility.

In a previous study, a passive sensor (HVAC) manikin coupled with a human thermal model was used to predict the thermal comfort of human test participants. The manikin was positioned among the test participants while they were collectively exposed to a mild transient heat up within a thermally asymmetric chamber. Ambient conditions were measured using the HVAC manikin’s distributed sensor system, which measures air velocity, air temperature, radiant heat flux, and relative humidity. These measurements were supplied as input to a human thermal model to predict thermophysiological response and subsequently thermal sensation and comfort. The model predictions were shown to accurately reproduce the group trends and the “time to comfort” at which a transition occurred from a state of thermal discomfort to comfort. In the current study, the effectiveness of using a coupled HVAC manikin-model system to evaluate a vehicle climate control system was investigated.

An electrically heated catalyst (EHC) in the three-way catalyst (TWC) aftertreatment system of a gasoline internal combustion engine (ICE) provides cold engine start exhaust pollutant emission reduction potential. The EHC can be started before switching on the ICE, thereby offering the possibility to pre-heat (PRH) the TWC, in the absence of exhaust flow. The EHC can also provide post engine start heat (PSH) when the heat is accompanied by exhaust mass flow over the TWC. A mixed heating strategy (MXH) comprises both PRH and PSH. All three strategies are evaluated under a range of engine start variations using an ICE-exhaust aftertreatment (EATS) simulation framework. It is driven by an engine speed-torque requested trace, with an engine-out emissions model focused on cold-start, engine heating and catalyst heating engine measures and a physics- based EATS with EHC model.

Many automotive electronic systems must be developed using a safety process. A preliminary hazard analysis is a first and an important step in such a process. This experimental study evaluates two methods for hazard identification using an electrical steering column lock system. Both methods are found to be applicable for hazard identification in an automotive context. It is also concluded that the induction with the failure modes method is less time consuming and easier to use than the method based on induction with generic low level hazards. Further, two proposals are presented to improve efficiency and consistency, reuse of generic hazards by component profiles and a domain specific catalogue of vehicle phases.

The evaporation of different fuels and fuel components in hollow-cone sprays at conditions similar to those at stratified cold start has been investigated using a combination of planar laser-induced fluorescence (LIF) and Mie scattering. Ketones of different volatility were used as fluorescent tracers for different fuel components in gasoline-like model fuels and ethanol-based fuels. LIF and Mie images were compared to evaluate to what extent various fuel components had evaporated and obtained a spatial distribution different from that of the liquid drops, as a function of fuel temperature and time after start of injection. A selective and sequential evaporation of fuel components of different volatility was found.

Centrifugal blowers serve as the primary source of airflow and aero-acoustic noise in automotive HVAC modules. Flow field measurements inside blowers indicate very complex flow patterns. A detailed flow visualization study was conducted on an actual HVAC fan module operated in water under dynamically similar conditions as those in air with the purpose of studying the complex flow patterns in order to improve the aerodynamic performance of the fan/scroll casing and diffuser components. Fan-scroll/diffuser interaction was also studied as function of fan speed. Conventional and special (shear thickening) dye injection flow visualization techniques were used to study the complex 3-dimensional vortical and unsteady flow patterns that occur in typical HVAC fans. A major advantage of the flow visualization technique using shear-thickening dye is its usefulness in high the Reynolds number flows that are typically encountered inside HVAC modules.

In order to meet emissions and power requirements, modern engine design has evolved in complexity and control. The cost and time restraints of calibration and testing of various control strategies have made virtual testing environments increasingly popular. Using Hardware-in-the-Loop (HiL), Volvo Penta has built a virtual test rig named VIRTEC for efficient engine testing, using a model simulating a fully instrumented engine. This paper presents an innovative Artificial Neural Network (ANN) based model for engine simulations in HiL environment. The engine model, herein called Artificial Neural Network Engine (ANN-E), was built for D8-600 hp Volvo Penta engine, and directly implemented in the VIRTEC system. ANN-E uses a combination of feedforward and recursive ANNs, processing 7 actuator signals from the engine management system (EMS) to provide 30 output signals.

Vehicle dynamics development relies on subjective assessments (SA), which is a resource-intensive procedure requiring both expert drivers and vehicles. Furthermore, development projects becoming shorter and more complex, and increasing demands on quality require higher efficiency. Most research in this area has focused on moving from physical to virtual testing. However, SA remains the central method. Less attention has been given to provide better tools for the SA process itself. One promising approach is to introduce computer-tablets to aid data collection, which has proven to be useful in medical studies. Simple software solutions can eliminate the need to transcribe data and generate more flexible and better maintainable questionnaires. Tablets’ technical features envision promising enhancements of SA, which also enable better correlations to objective metrics, a requirement to improve CAE evaluations.