Search Results

Air conditioning acoustics have become of paramount importance in electric vehicles, where noise from electromechanical components is no longer masked by the presence of the internal combustion engine. In a car HVAC systems, the coolant compressor is one of the most important sources in terms of vibration and noise generation. The paper, the generated structural noise is studied in detail on a prototype installation, and the noise transmission and propagation mechanisms are analyzed and discussed. Through ”in situ” measurements and virtual point transformation, the rotor unbalance forces and torque acting within the component are identified. The dynamic properties of the rubber mounts, installed between the compressor and its support, are identified thanks to matrix inversion methods. To assess the quality of the proposed procedure, the synthesized sound pressure level is compared with experimental SPL measurements in different operational conditions.

Heavy Duty Vehicle (HDV) Diesel emission regulations are set to be tightened in the future. The introduction of PN PEMS testing for Euro VI-e, and the expected tightening of PM/NOx targets set to be introduced by CARB in the US beyond 2024 are expected to create challenging tailpipe PN conditions for OEMs. Additionally, warranty and the useful life period will be extended from current levels. Improved fuel efficiency (reduction of CO2) also remains an important performance criteria. Furthermore, future non-road diesel emission regulations may follow tighten HDV diesel emission regulations contents, and non-road cycles evaluation needs to be considered as well for future. In response to the above tightened regulation, for Diesel Particulate Filter (DPF) technologies will require higher PN filtration performance, lower pressure drop, higher ash capacity and better pressure drop hysteresis for improved soot detectability.

Selective catalyst reduction (SCR) using cordierite honeycomb substrate is generally used as a DeNOx catalyst for diesel engines exhaust in both on-road and commercial off-highway vehicles to meet today’s worldwide emission regulations. Worldwide NOx emission regulations will become stricter, as represented by CARB2027 and EuroVII. Technologies which can achieve further lower NOx emissions are required. Recently, several technologies, like increased SCR catalyst loading amount on honeycomb substrates, and additional SCR catalyst volume in positions closer to the engine are being considered to achieve ultra-low NOx emissions. However, undesirable pressure drop increase and enlarging after treatment systems will be caused by adopting these technologies. Therefore, optimization of the material and honeycomb cell structure for SCR is inevitable to achieve ultra-low NOx emissions, while minimizing any system drawbacks.

It is particularly easy to get tunnel vision as a domain expert, and focus only on the improvements one could provide in their area of expertise. To make matters worse, many Original Equipment Manufacturers (OEMs) are silo-ed by domain of expertise, unconsciously promoting this single mindedness in design. Unfortunately, the successful and profitable development of a vehicle is dependent on the delicate balance of performance across many domains, involving multiple physics and departments. Taking for instance the design of a Heating, Ventilation & Air Conditioning (HVAC) system, the device’s primary function is to control the climate system in vehicle cabins, and more importantly to make sure that critical areas on the windshield can be defrosted in cold weather conditions within regulation time. With the advent of electric and autonomous vehicles, further importance is now also placed on the energy efficiency of the HVAC, and its noise.

The reduction of vehicle exhaust particle emissions is a success story of European legislation. Various particle number (PN) counters and calibration procedures serve as tools to enforce PN emission limits during vehicle type approval (VTA) or periodical technical inspection (PTI) of in-use vehicles. Although all devices and procedures apply to the same PN-metric, they were developed for different purposes, by different stakeholder groups and for different target costs and technical scopes. Furthermore, their calibration procedures were independently defined by different stakeholder communities. This frequently leads to comparability and interpretation issues. Systematic differences of stationary and mobile PN counters (PN-PEMS) are well-documented. New, low-cost PTI PN counters will aggravate this problem. Today, tools to directly compare different instruments are scarce.

This paper describes a novel approach for modeling an automotive HVAC unit. The model consists of black-box models trained with experimental data from a self-developed measurement setup. It is capable of predicting the temperature and mass flow of the air entering the vehicle cabin at the various air vents. A combination of temperature and velocity sensors is the basis of the measurement setup. A measurement fault analysis is conducted to validate the accuracy of the measurement system. As the data collection is done under fluctuating ambient conditions, a review of the impact of various ambient conditions on the HVAC unit is performed. Correction models that account for the different ambient conditions incorporate these results. Numerous types of black-box models are compared to identify the best-suited type for this approach. Moreover, the accuracy of the model is validated using test drive data.

Autonomous driving systems and connected mobility are the next big developments for the car manufacturers and their suppliers during the next decade. To achieve the high computing power needs and fulfill new upcoming requirements due to functional safety and security, heterogeneous processor architectures with a mixture of different core architectures and hardware accelerators are necessary. To tackle this new type of hardware complexity and nevertheless stay within monetary constraints, high performance computers, inspired by state of the art data center hardware, could be adapted in order to fulfill automotive quality requirements. The European Processor Initiative (EPI) research project tries to come along with that challenge for next generation semiconductors. To be as close as possible to series development needs for the next upcoming car generations, we present a hybrid semiconductor system-on-chip architecture for automotive.

In order to meet the challenging CO2 targets beyond 2020 without sacrificing performance, Gasoline Direct Injection (GDI) technology, in combination with turbo charging technology, is expanding in the automotive industry. However, while this technology does provide a significant CO2 reduction, one side effect is increased Particle Number (PN) emission. As a result, from September 2017, GDI vehicles in Europe are required to meet the stringent PN emission limits of 6x1011 #/km under the Worldwide harmonized Light vehicles Test Procedure (WLTP). In addition, it is required to meet PN emission of 9x1011 #/km under Real Driving Emission (RDE) testing, which includes a Conformity Factor (CF) of 1.5 to account for current measurement inaccuracies on the road. This introduction of RDE testing in Europe and China will especially provide a unique challenge for the design of exhaust after-treatment systems due to its wide boundary conditions.

In this paper a method for the identification of most significant vehicle parameters influencing the behavior of a lateral control system of autonomous car is presented. Requirements for the design stage of the controller need to consider many uncertainties in the plant. While most vehicle properties can be compensated by an appropriate tuning of the control parameters, other vehicle properties can change significantly during usage. The control system is evaluated based on performance measures. Analyzed parameters comprise functional tire characteristics, mass of the vehicle and position of its center of gravity. Since the parameters are correlated, but Sobol’ sensitivity analysis assumes decorrelated inputs, random variation yields no reasonable results. Furthermore, the variation of each parameter or set of parameters is not applicable since the numbers of required simulations is increased significantly according to input dimension.

External Exhaust Gas Recirculation (EGR) provides an opportunity to increase the efficiency of turbocharged spark-ignition engines. Of the competing technologies and configurations, Low-Pressure EGR (LP-EGR) is the most challenging in terms of its dynamic behavior. Only some of the stationary feasible potential can be used during dynamic engine operation. To guarantee fuel consumption-optimized engine operation with no instabilities, a load point-dependent limitation of the EGR rate or alternatively an adaptation of the operating point to the actual EGR rate is crucial. For this purpose, a precise knowledge of efficiency and combustion variance is necessary. Since the operating state includes the actual EGR rate, it has an additional dimension, which usually results in an immense measuring effort.

With the push towards more stringent on-road US heavy duty diesel regulations (i.e. HD GHG Phase 2 and the proposed ARB 20 mg/bhp-hr NOx), emission system packaging has grown critical while improving fuel economy and NOx emissions. The ARB regulations are expected to be implemented post 2023 while regulation for EU off-road segment will begin from 2019. The regulation, called Stage V, will introduce particle number (PN) regulation requiring EU OEMs to introduce a diesel particulate filter (DPF) while customer demands will require the OEMs to maintain current emission system packaging. A viable market solution to meet these requirements, especially for EU Stage V being implemented first, is a DPF coated with a selective catalyst reduction (SCR) washcoat (i.e. SCRonDPF).

In order to meet the challenging CO2 targets beyond 2020 despite keeping high performance engines, Gasoline Direct Injection (GDI) technology usually combined with charged aspiration is expanding in the automotive industry. While providing more efficient powertrains to reduce fuel consumption one side effect of GDI is the increased particle formation during the combustion process. For the first time for GDI from September 2014 there is a Particle Number (PN) limit in EU of 6x10 sup 12 #/km, which will be further reduced by one order of magnitude to 6x10 sup 11 #/km effective from September 2017 to be the same level as applied to Diesel engines. In addition to the PN limit of the certification cycle NEDC further certification of Real Driving Emissions (RDE) including portable PN measurements are under discussion by the European Commission. RDE test procedure requires stable and low emissions in a wide range of engine operations and durable over a distance of 160 000 km.

With the increased use of engines utilizing direct fuel injection and the upcoming introduction of more stringent emissions legislation that regulates not only particulate mass (PM) but also particulate number (PN), the emissions from Direct Injection Spark Ignition Engines (DISI) are an increasing concern. Gasoline Particle Filters (GPF) represent a potential way to reduce particle number emissions from DISI engines and are particularly effective considering the tough performance requirements during cold start and over RDE operation. Even though some learning from the development and application of particulate filters to diesel engines can be transferred to gasoline engines, the particle composition, mass to number ratio as well as the exhaust gas temperature and composition from gasoline engines are significantly different to diesel engines. Therefore, there is the need to study the application of particulate filters to gasoline engines in more depth.

Current regulatory developments aim for stricter emission limits, increased environmental protection and purification of air on a local and global scale. In order to find solutions for a cleaner combustion process, it is necessary to identify the critical components and parameters responsible for the formation of emissions. This work provides an evaluation process for particle formation during combustion of a modern direct injection engine, which can help to create new aftertreatment techniques, such as a gasoline particle filter (GPF) system, that are fit for purpose. With the advent of “real driving emission” (RDE) regulations, which include market fuels for the particulate number testing procedure, the chemical composition and overall quality of the fuel cannot be neglected in order to yield a comparable emission test within the EU and worldwide.

Over the past decades, interior noise from wind noise or engine noise have been significantly reduced by leveraging improvements of both the overall vehicle design and of sound package. Consequently, noise sources originating from HVAC systems (Heat Ventilation and Air Conditioning), fans or exhaust systems are becoming more relevant for perceived quality and passenger comfort. This study focuses on HVAC systems and discusses a Flow-Induced Noise Detection Contributions (FIND Contributions) numerical method enabling the identification of the flow-induced noise sources inside and around HVAC systems. This methodology is based on the post-processing of unsteady flow results obtained using Lattice Boltzmann based Method (LBM) Computational Fluid Dynamics (CFD) simulations combined with LBM-simulated Acoustic Transfer Functions (ATF) between the position of the sources inside the system and the passenger’s ears.

Ammonia Selective Catalytic Reduction (SCR) is adapted for a variety of applications to control nitrogen oxides (NOx) in diesel engine exhaust. The most commonly used catalyst for SCR in established markets is Cu-Zeolite (CuZ) due to excellent NOx conversion and thermal durability. However, most applications in emerging markets and certain applications in established markets utilize vanadia SCR. The operating temperature is typically maintained below 550°C to avoid vanadium sublimation due to active regeneration of the diesel particulate filter (DPF), or some OEMs may eliminate the DPF because they can achieve particulate matter (PM) standard with engine tuning. Further improvement of vanadia SCR durability and NOx conversion at low exhaust gas temperatures will be required in consideration of future emission standards.

A local Gaussian process regression approach is presented, which allows to model nonlinearities of internal combustion engines more accurate than global Gaussian process regression. By building smaller models, the prediction of local system behavior improves significantly. In order to predict a value, the algorithm chooses the nearest training points. The number of chosen training points depends on the intensity of estimated nonlinearity. After determining the training points, a model is built, the prediction performed and the model discarded. The approach is demonstrated with a benchmark system and air charge test bed measurements. The measurements are taken from a turbocharged SI gasoline engine with both variable inlet valve lift and variable inlet and exhaust valve opening angle. The results show how local Gaussian process regression outmatches global Gaussian process regression concerning model quality and nonlinearities in particular.

Air charge calibration of turbocharged SI gasoline engines with both variable inlet valve lift and variable inlet and exhaust valve opening angle has to be very accurate and needs a high number of measurements. In particular, the modeling of the transition area from unthrottled, inlet valve controlled resp. throttled mode to turbocharged mode, suffers from small number of measurements (e.g. when applying Design of Experiments (DoE)). This is due to the strong impact of residual gas respectively scavenging dominating locally in this area. In this article, a virtual residual gas sensor in order to enable black-box-modeling of the air charge is presented. The sensor is a multilayer perceptron artificial neural network. Amongst others, the physically calculated air mass is used as training data for the artificial neural network.

Diesel engines are widely used to reduce CO2 emission due to its higher thermal efficiency over gasoline engines. Considering long term CO2 targets, as well as tighter gas emission, especially NOx, diesel engines must become cleaner and more efficient. However, there is a tradeoff between CO2 and NOx and, naturally, engine developers choose lower CO2 because NOx can be reduced by a catalytic converter, such as a SCR catalyst. Lower CO2 engine calibration, unfortunately, leads to lower exhaust gas temperatures, which delays the activation of the catalytic converter. In order to overcome both problems, higher engine out NOx emission and lower exhaust gas temperatures, close-coupled a diesel particulate filter (DPF) system with integration of SCR catalyst technology is preferred. For SCR catalyst activity, it is known that the catalyst loading amount has an influence on NOx performance, so a high SCR catalyst loading will be required.

Since the implementation of Euro 6 in September 2014, diesel engines are facing another drastic reduction of NOx emission limits from 180 to only 80 mg/km during NEDC and real driving emissions (RDE) are going to be monitored until limit values are enforced from September 2017. Considering also long term CO2 targets of 95 g/km beyond 2020, diesel engines must become cleaner and more efficient. However, there is a tradeoff between NOx and CO2 and, naturally, engine developers choose lower CO2 because NOx can be reduced by additional devices such as EGR or a catalytic converter. Lower CO2 engine calibration, unfortunately, leads to lower exhaust gas temperatures, which delays the activation of the catalytic converter. In order to overcome both problems, higher NOx engine out emission and lower exhaust gas temperatures, new aftertreatment systems will incorporate close-coupled DeNOx systems.