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The efforts of the ISO “Test Variability Task Force” have been aimed at improving the understanding and at reducing brake dynamometer test variability during performance testing. In addition, dynamometer test results have been compared and correlated to vehicle testing. Even though there is already a vast amount of anecdotal evidence confirming the fact that different procedures generate different friction coefficients on the same brake corner, the availability of supporting data to the industry has been elusive up to this point. To overcome this issue, this paper focuses on assessing friction levels, friction coefficient sensitivity, and repeatability under ECE, GB, ISO, JASO, and SAE laboratory friction evaluation tests.

This paper proposes and evaluates improvements to a crash simulation of a fuel delivery module in a fuel tank. The simulations were performed in ANSYS/LS-DYNA. Deviations between the original simulation and test data were studied and reasons for the deviations hypothesized. These reasons stemmed from some of the simplifying assumptions of the model. Improvements consisted of incorporating plasticity and strain rate effects into the material models. Performance criteria were also directly incorporated into the material models such that non-performing portions of the model could be deactivated during the simulation. Finally, solid-fluid interactions were added into the simulation to include the momentum transfer from fuel to the fuel delivery module. It was previously thought that effects of a crash would be most severe on the module when the fuel tank was empty and the module was full with fuel.

Networking of active and passive safety is the fundamental basis for comprehensive vehicle safety. Situation-relevant information relating to driver reactions, vehicle behavior and traffic environment are fed into a crash probability calculator, which continually assesses the current crash risk and intervenes when necessary with appropriate measures to avoid a crash and reduce potential injuries. This provides effective protection not only for vehicle occupants but also for other, vulnerable road users. As this functionality up till now only relates to the vehicle itself, the next logical step is enhancement leading to the ultimate goal in safety performance, telematics. The integration of this embedded, in-vehicle wireless communication system allows Car-to-Car (C2C) and Car-to-Infrastructure (C2I) functionality for, e.g. hazard warning. This is an integral element of the cascaded ContiGuard® protection measures.

The AUTomotive Open System ARchitecture (AUTOSAR) Development Partnership has published early 2008 the specifications Release 3.0 [1], with a prime focus on the overall architecture, basic software, run time environment, communication stacks and methodology. Heavy developments have taken place in the OEM and supplier community to deliver AUTOSAR loaded cars on the streets starting 2008 [2]. The 2008 achievements have been: Improving the specifications in order to secure the exploitation for body, chassis and powertrain applications Adding major features: safety related functionalities, OBD II and Telematics application interfaces.

A high voltage battery is an essential part of hybrid electric vehicles (HEVs). It is imperative to precisely estimate the state of charge (SOC) and state of health (SOH) of battery in real time to maintain reliable vehicle operating conditions. This paper presents a method of estimating SOC and SOH through the incorporation of current integration, voltage translation, and Ah-throughput. SOC estimation utilizing current integration is inadequate due to the accumulation of errors over the period of usage. Thus voltage translation of SOC is applied to rectify current integration method which improves the accuracy of estimation. Voltage translation data is obtained by subjecting the battery to hybrid pulse power characterization (HPPC) test. The Battery State of Health was determined by semi-empirical model combined with accumulated Ah-throughput method. Battery state of charge was employed as an input to estimate damages accumulated to battery aging through a real-time model.

This paper presents results on how the Equivalent Consumption Minimization Strategy (ECMS) penalty factor effects Lithium ion battery aging. The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’. Vehicle simulation using multiple combinations of highway and city drive cycles. For each combination of drive cycles, six ECMS penalty factor values are used. Battery aging is evaluated using a semi-empirical model combined with accumulated Ah-throughput method which uses, as an input, the battery state of charge trajectory from the vehicle simulations. The tradeoff between fuel cost and battery aging cost is explicitly displayed. In addition, the results provide insight into how driving behavior affects battery aging. The paper concludes with a discussion of the optimal balance between fuel cost and battery aging.

In the research project between the Institute of Automotive Engineering (FZD) of the Technische Universität Darmstadt (TUD) and Continental Teves AG & Co. oHG a new modeling concept has been developed. With the aim to enhance the current development process, the brake caliper is modeled based on coupled rigid bodies integrated into a nonlinear system model. Using an explicit interface definition, the number of degrees of freedom is minimized and the calculation of caliper performance is possible over a wide range of parameters. Compared to models based on the Finite Element Method (FEM), fully parameterized geometry from CAD is not necessary, thus the caliper can be optimized for a variation of its geometrical and physical parameters. With this modeling approach, typical performance criteria such as caliper fluid displacement, hysteresis, uneven pad wear and residual torque can be calculated in a virtual bench test.

Automotive manufacturers are requiring lightweight materials, including glazing materials to improve vehicle fuel economy and meet government mandates. Taken as a group, the area of four side windows is comparable to that of a windshield, and, therefore, can offer significant weight reduction opportunities. As glass thickness is reduced, the acoustic and stiffness properties of the glazing change. Newer developmental interlayer materials have demonstrated the capability for overcoming the reduction in performance to maintain the properties of the original heavier constructions.

The US American government introduced a law to mandatorily equip passenger vehicles with rear view cameras. Furthermore, US NCAP presented a test for passenger vehicles to brake on pedestrians while back up. These two circumstances lead to main motivation of the development of the Comfort Backup Assist (CBUA). Nevertheless, more and more passenger cars in general are being equipped with rear view cameras. Rear view system (RVS) allows to deliver a rear-view camera system including a braking functionality which is intended to make the driving mission safer and reduce the number of accidents in parking driving situations. RVS also focus on vehicle safety by reducing accidents while taking reversing/parking scenarios and to provides slow de-acceleration of the vehicle gradually to avoid jerk and increase the ride comfort.

Optical imaging diagnostics of combustion are most often performed in the visible spectral band, in part because camera technology is most mature in this region, but operating in the infrared (IR) provides a number of benefits. These benefits include access to emission lines of relevant chemical species (e.g. water, carbon dioxide, and carbon monoxide) and obviation of image intensifiers (avoiding reduced spatial resolution and increased cost). High-speed IR in-cylinder imaging and image processing were used to investigate the relationships between infrared images, quantitative image-derived metrics (e.g. location of the flame centroid), and measurements made with in-cylinder pressure transducers (e.g. coefficient of variation of mean effective pressure). A 9.7-liter, inline-six, natural-gas-fueled engine was modified to enable exhaust-gas recirculation (EGR) and provide borescopic optical access to one cylinder for two high-speed infrared cameras.

Driver assistance features have been introduced to the market focusing on basic, independent functional scenarios. The trend is showing that these kinds of products are facing more and more complex scenarios and we are transitioning from single independent functions to a strongly networked system. Some of the drivers for future autonomous vehicles are 360° monitoring by active safety technology and V2X (vehicle to vehicle or vehicle to infrastructure) communication. In the past vehicles were strictly operated by the driver. Advanced driver assistance products added so called feedback features like lane departure warning, forward collision warning, and blind spot monitoring. First steps towards semi-autonomous driving started with the development of active support functions like adaptive cruise control or lane keeping support. Collision mitigation with various authority levels is the next milestone towards automation followed by other, even more advanced, features.

On-road emission measurements of 23 VN-trucks on a randomly chosen driving cycle, consisting of 10 miles two-lane and 8 miles four-lane road, showed tailpipe NOx emissions on fleet average of 0.96 g/bhp-hr, or 1.06 g/bhp-hr when including the time the exhaust gas temperature was below 200°C. Complementary measurements in a SET-cycle (13 point OICA -cycle) on a chassis dynamometer showed a tailpipe emission of 0.008 g PM per bhp-hr. Moreover, cost analysis show that the diesel fuel consumption remains unchanged whether the truck running on ULSD is equipped with a Combined Exhaust gas AfterTreatment System (CEATS) installed or not.

This paper presents a novel encoding scheme as an alternative to Analog amplitude encoding for communicating sensor signals. The scheme has the potential of becoming a non-proprietary industrial standard for communicating sensor information to electronic control modules. Key features of the encoding scheme are the ability to communicate two sensor values using only 3 wires (power, ground and signal) with 12 bit resolution within 1ms. The scheme includes a checksum for error detection and a mechanism for reporting serial data such as low rate sensor information, part numbers or fault codes. Data is communicated to the receiving module by varying the time between discrete (single edge polarity) transitions. The encoding is self-calibrating and does not require an expensive crystal in the sending module (assumed to be a low-cost ASIC) to maintain signal integrity.

This is an extension of simple fuel consumption modeling toward HEV. Previous work showed that in urban driving the overhead of running an ICEV engine can use as much fuel as the traction work. The bidirectional character and high efficiency of electric motors enables HEVs to run as a BEV at negative and low traction powers, with no net input from the small battery. The ICE provides the net work at higher traction powers where it is most efficient. Whereas the network reduction is the total negative work times the system round-trip efficiency, the reduction in engine running time requires knowledge of the distribution of traction power levels. The traction power histogram, and the work histogram derived from it, provide the required drive cycle description. The traction power is normalized by vehicle mass, so that the drive trace component becomes invariant, and the road load component nearly invariant to vehicle mass.

In the automotive embedded system domain, the measurements from vehicle and Hardware-In-Loop are currently evaluated against the testcases, either manually or via automation scripts. These evaluations are localized; they evaluate a limited number of signals for a particular measurement without considering system-level behavior. This results in defect leakage. This study aims to develop a tool that can notify anomalies at the signal level in a new measurement without referring to the testcases, considering a more significant number of system-level signals, thereby significantly reducing the defect leakage. The tool learns important features and patterns of each maneuver from many historical measurements using deep learning techniques. We tried two CNN (convolution neural network) models. The first one is a specially designed CNN that does this maneuver classification and class-specific feature extraction.

Natural gas (NG) is attractive for heavy-duty (HD) engines for reasons of cost stability, emissions, and fuel security. NG cannot be reliably compression-ignited, but conventional gasoline ignition systems are not optimized for NG and are challenged to ignite mixtures that are lean or diluted with exhaust-gas recirculation (EGR). NG ignition is particularly challenging in large-bore engines, where completing combustion in the available time is more difficult. Using two high-speed infrared (IR) cameras with borescopic access to one cylinder of an HD NG engine, the effect of ignition system on the early flame-kernel development and cycle-to-cycle variability (CCV) was investigated. Imaging in the IR yielded strong signals from water emission lines, which located the flame front and burned-gas regions and obviated image intensifiers. A 9.7-liter, six-cylinder engine was modified to enable exhaust-gas recirculation and to provide optical access.

Compressed natural gas (CNG) is an attractive, alternative fuel for spark-ignited (SI), internal combustion (IC) engines due to its high octane rating, and low energy-specific CO2 emissions compared with gasoline. Directly-injected (DI) CNG in SI engines has the potential to dramatically decrease vehicles’ carbon emissions; however, optimization of DI CNG fueling systems requires a thorough understanding of the behavior of CNG jets in an engine environment. This paper therefore presents an experimental and modeling study of DI gaseous jets, using methane as a surrogate for CNG. Experiments are conducted in a non-reacting, constant volume chamber (CVC) using prototype injector hardware at conditions relevant to modern DI engines. The schlieren imaging technique is employed to investigate how the extent of methane jets is impacted by changing thermodynamic conditions in the fuel rail and chamber.

This paper presents a novel approach to augment existing engine calibrations to deliver improved engine performance during a transient, through the application of multi-objective optimization techniques to the calibration of the Variable Valve Timing (VVT) system of a 1.0 litre gasoline engine. Current mature calibration approaches for the VVT system are predominantly based on steady state techniques which fail to consider the engine dynamic behaviour in real world driving, which is heavily transient. In this study the total integrated fuel consumption and engine-out NOx emissions over a 2-minute segment of the transient Worldwide Light-duty Test Cycle are minimised in a constrained multi-objective optimisation framework to achieve an updated calibration for the VVT control. The cycle segment was identified as an area with high NOx emissions.

Mainly due to environmental regulation, future Engine Control Unit (ECU) will be equipped with in-cylinder pressure sensors. The introduction of this innovative solution has increased the number of involved variables, requiring an unceasing improvement in the modeling approaches and in the computational capabilities of Engine Control Unit (ECU). Hardware in the Loop (HIL) test system therefore has to provide in-cylinder pressure in real time from an adequate model. This paper describes a synthesis of our study targeted to the development of in-cylinder crank angle combustion model excluding look up tables, dedicated to HIL test bench. The main objective of the present paper is a comprehensive analysis of a reduced combustion model, applied to a direct injection Diesel engine at varying engine operating range, including single injection and multi injection strategies.

Accuracy of clutch torque model which converts target torque to target stroke is essential to control the dry clutch system. Continuous Adaptation algorithm requires micro slip control during in-gear driving. Clutch judder during micro slip control can cause detrimental effect on the output of controller as slip speed is calculated by deviation of engine speed and clutch speed. Conventional approach to avoid clutch judder is using low pass filter to the input of controller which is slip speed. But this affect to the overall response time of slip controller. In this paper, signal processing algorithm is design and tested for the clutch speed(Input shaft speed). With low pass filter in clutch speed, clutch judder signal is decreased but overall time delay creates static error during acceleration. Several phase advance algorithm is designed to overcome the static error during acceleration without disadvantage of decreasing clutch judder signal.