Search Results

The development of hydrogen-fueled vehicles has created the need for established fuel consumption testing methods. Until now the EPA has only accepted three methods of hydrogen fuel consumption testing, gravimetric, PVT (stabilized pressure, volume and temperature), and Coriolis mass flow; all of which necessitate physical measurements of the fuel supply [1]. BMW has developed an equation and subsequent testing methods to accurately and effectively determine hydrogen fuel consumption in light-duty vehicles using only exhaust emissions. Known as “Hydrogen-Balance”, the new equation requires no changes to EPA procedures and only slight modifications to most existing chassis dynamometers and CVS (Constant Volume Sampling) systems. The SAE 2008-01-1036, also written by BMW, explains the background as well as required equipment and changes to the CVS testing system. This paper takes hydrogen balance further by testing it against the three EPA established forms of fuel consumption.

The Hydrogen-Balance equation makes it possible to calculate the fuel economy or fuel consumption of hydrogen powered vehicles simply by analyzing exhaust emissions. While the benefits of such a method are apparent, it is important to discuss possible influencing factors that may decrease Hydrogen-Balance accuracy. Measuring vehicle exhaust emissions is done with a CVS (Constant Volume Sampling) system. While the CVS system has proven itself both robust and precise over the years, utilizing it for hydrogen applications requires extra caution to retain measurement accuracy. Consideration should be given to all testing equipment, as well as the vehicle being tested. Certain environmental factors may also play a role not just in Hydrogen-Balance accuracy, but as also in other low emission testing accuracy.

More than ever, microcontroller performance in cars has a direct impact on the driving experience, on compliance with improved safety, ever-stricter emissions regulations, and on fuel economy. The simple microcontrollers formerly used in automobiles are now being replaced by powerful number-crunchers with incredible levels of peripheral integration. As a result, performance can no longer be measured in MIPS (Millions of Instructions Per Second). A microcontroller's effectiveness is based on coherent partitioning between analog and digital, hardware and software, tools and methodology. To make an informed choice among the available devices, the designer needs benchmarks that are specific to automotive applications, and which provide a realistic representation of how the device will perform in the automotive environment.

More than ever, microcontroller performance in cars has a direct impact on the driving experience, on compliance with improved safety, ever-stricter emissions regulations, and on fuel economy. The simple microcontrollers formerly used in automobiles are now being replaced by powerful number-crunchers whose performance can no longer be measured in MIPS. Instead, their effectiveness is based on a coherent partitioning between analog and digital, hardware and software, tools and methodology. To make an informed choice among the available devices, what the designer needs are benchmarks that are specific to automotive applications, and which provide a realistic representation of how the device will perform in the automotive environment. This presentation will explore the role of new benchmarks in the development of complex automotive applications.

Increasingly stringent requirements to improve fuel economy and reduce emissions are pushing the automotive industry toward more innovative solutions. To fulfill the demand, OEMs are developing hybrid systems with powerful electronics. The key technology is in all cases the battery. It is the most critical and expensive element of hybrid systems. The battery requires special care, as it must supply up to 400 Volts (V) and have a capacity of up to several kilowatt-hours (kWh). This paper will review the main functions of a Lithium-ion (Li-ion) battery management system, including power on/off, charging/discharging, and computation of the state of charge and state of health. In order to increase the battery lifespan, new functions such as active load balancing must be implemented.

Although hydrogen ICE engines have existed in one sort or another for many years, the testing of fuel consumption by way of exhaust emissions is not yet a proven method. The current consumption method for gasoline- and diesel-fueled vehicles is called the Carbon-Balance method, and it works by testing the vehicle exhaust for all carbon-containing components. Through conservation of mass, the carbon that comes out as exhaust must have gone in as fuel. Just like the Carbon-Balance method for gas and diesel engines, the new Hydrogen-Balance equation works on the principle that what goes into the engine must come out as exhaust components. This allows for fuel consumption measurements without direct contact with the fuel. This means increased accuracy and simplicity. This new method requires some modifications to the testing procedures and CVS (Constant Volume Sampling) system.

The increasingly stringent requirements in relation to emission reduction and onboard diagnostics are pushing the Chinese automotive industry toward more innovative solutions and a rapid increase in electronic control performance. To manage the system complexity the architecture will require being well structure on hardware and software level. The paper introduces GEMS-K1 (Gasoline Engine Management System - Kit 1). GEMS-K1 is a platform being compliant with Euro IV emission regulation for gasoline engines. The application software is developed using modeling language, the code is automatically generated from the model. The driver software has a well defined structure including microcontroller abstraction layer and ECU abstraction layer. The hardware is following design rules to be robust, 100% testable and easy to manufacture. The electronic components use the latest innovation in terms of architecture and technologies.

The number of vehicles in world has been steadily increasing over the years. Asia Pacific is blessed to have the fastest growth rate in the world, with China experiencing over 20% vehicle production growth in the recent and coming years. As India jumps on this explosive bandwagon which could see growth rates higher than China, there is a need to understand the environmental and cost aspects arising from the vast increase of automobiles. The need to protect the environment, combined with the limited resource of oil, has led to the need for more fuel-efficient vehicles with intelligent engine and transmission control systems. This paper/presentation will look into the tough emissions regulations, lower CO2 requirement, different fuels and their efficiency, alternative fuel and the infrastructure to support such a paradigm shift, cost to achieve the desired, and GEMS-K1 (Gasoline Engine Management System - Kit 1) as a solution to meet some of the issues mentioned.

The results of previous Life Cycle Assessments indicate the ecological dominance of the vehicle's use phase compared to its production and recycling phase. Particularly the so-called weight-induced fuel saving coefficients point out the great spectrum (0.15 to 1.0 l/(100 kg · 100 km)) that affects the total result of the LCA significantly. The objective of this article, therefore, is to derive a physical based, i.e. scientific chargeable and practical approved, concept to determine the significant parameters of a vehicle's use phase for the Life Cycle Inventory. It turns out that - besides the aerodynamic and rolling resistance parameters and the efficiencies of the power train - the vehicle's weight, the rear axle's transmission ratio and the driven velocity profile have an important influence on a vehicle's fuel consumption.

The increasing legal requirements for safety, emission reduction, fuel economy and onboard diagnosis systems push the market for more innovative solutions with rapidly increasing complexity. Hence, the embedded systems that will have to control the automobiles have been developed at such an extent that they are now equivalent in scale and complexity to the most sophisticated avionics systems. This paper will demonstrate the key elements to provide a powerful, scalable and configurable solution that offers a migration pass to evolution and even revolution of automotive Sensors and Sensor interfaces. The document will explore different architectures and partitioning. Sensor technologies such as magnetic field sensors based on the hall effect as well as bulk and surface silicon micro machined sensors will be mapped to automotive applications by examples. Functions such as self-test, self-calibration and self-repair will be developed.

The increasing legal requirements for safety, emission reduction, fuel economy and onboard diagnosis systems is pushing the market for more innovative solutions with rapidly increasing complexity. Hence, the embedded systems that will have to control the automobiles have been developed at such an extent that they are now equivalent in scale and complexity to the most sophisticated avionics systems. The former analogue filter design is now replaced by digital signal processing. This paper will demonstrate the key elements to provide a powerful, scalable and configurable solution that offers a migration route to evolve and even revolutionize automotive electronics. To illustrate this migration toward digital processing the knock function has been developed. A simple RC filter is used as external anti-aliasing. To get the maximum flexibility the signal is very early converted and processed digitally. The micro-controller has been developed using a three-layered solution.

As the demand for enhanced comfort, safety and differentiation with new features continues to grow and as electronics and software enable most of these, the number of electronic units or components within automobiles will continue to increase. This will increase the overall system complexity, specifically with respect to the number of controller actuators such as e-motors. However, hard constraints on cost and on physical boundaries such as maximum power dissipation per unit and pin-count per unit/connector require new solutions to alternative system partitioning. Vehicle manufacturers, as well as system and semiconductor suppliers are striving for increased scalability and modularity to allow for most cost optimal high volume configurations while featuring platform reuse and feature differentiation. This paper presents new semiconductor based approaches with respect to technologies, technology mapping and assembly technologies.

Increasing fuel costs and emission regulations force the car manufacturers to develop powerful but efficient engines. The 3-liter car (3-liter/100 km fuel consumption → 80 miles/gallon) is one of the slogans. To fulfill these requirements a fully electronic controlled Engine Management is necessary. Carburetor systems are replaced by fuel injection systems. Direct injection for Diesel as well as for gasoline engines is the clear trend for the future. The mechanical throttle systems, used for a long time will not fit to the requirements of direct injection. A DC motor for electronic throttle control in conjunction with λ regulation and exhaust gas recirculation are the key elements for low emission cars. Also the automotive ignition system is in a process of change today.

Fuel efficiency and clean combustion engine versus high engine performance - which will increase up to factor 10 in the next 5 years - with less engine displacement are driving more complex engine control systems in today's and future vehicles. The challenge is not only to design a perfect engine, but also to incorporate the right semiconductors. Beside this demand on high sophisticated electronics the demand on cost reduction - especially for small cars - is one driving factor for a smart partitioning. Infineon offers sensors, microcontrollers and power semiconductors for today's engine management platforms and therefore owns the right technologies to manufacture those devices. This opens up the possibility to integrate more functionality in less devices as in today's partitioning or to define electronics to simplify complex control strategies and to optimize the performance of each device.

A mechatronic approach to implementing a BLDC motor drive control system is described. The partitioning method used allows the motor power to be scaled from around 100 watts to 1 kilowatt. The chosen approach maps the required electronic functionality to different existing front-end technologies. By drawing on vast experience with back-end technologies, especially chip-on-chip assembly, it is possible to implement a system in a one-package solution. The advantages of each technology are used to achieve a cost-effective, space-saving solution.

An innovative way of lowering engine fuel consumption is to reduce engine displacement. However, smaller engines featuring reduced swept volume typically exhibit insufficient torque at low engine speeds. Conventional exhaust turbochargers are not able to compensate for this behavior and additionally suffer from the familiar turbo lag. One possible solution may be an electrically assisted turbocharger, with a high-speed motor providing the extra boost at low engine speeds. A critical factor for the efficiency of the concept is the ratio of the electric motor torque and the rotational mass inertia of the rotor. Testbench evaluation shows acceleration times of 0.5 seconds to reach speeds up to 70,000 rpm. Typically, the electrical load of such systems goes up to 3 kW. Target motors are various types of electrically commutated motors such as BLDC, switched reluctance or induction motors.

Flame Ionization Detectors (FID) can be used to detect organic hydrocarbons that occur in plastics, lacquers, adhesives, solvents and gasoline. These substances are ionized in the hydrogen flame of the FID. The ionization current that is produced depends on the amount of hydrocarbon in the sample. With the lowering of emissions limits, measuring instruments, including the FID, have to be able to detect very low values. For SULEV (Super-Ultra Low Emissions Vehicle) measurements the accuracy and also the general applicability of the CVS (Constant Volume Sampling) measuring technique are now questioned. Basic understanding is necessary to ask the right questions. One important issue is the science behind the measurement principle of the FID. And in this case especially the influence of contamination of the operating gases, cross sensitivity and data processing on the Limit of Detection (LOD).

The Energy and Environment Test Centre (EVZ) is a complex comprising three large climatic wind tunnels, two smaller test chambers, nine soak rooms and support infrastructure. The capabilities of the wind tunnels and chambers are varied, and as a whole give BMW the ability to test at practically all conditions experienced by their vehicles, worldwide. The three wind tunnels have been designed for differing test capabilities, but share the same air circuit design, which has been optimized for energy consumption yet is compact for its large, 8.4 m₂, nozzle cross-section. The wind tunnel test section was designed to meet demanding aerodynamic specifications, including a limit on the axial static pressure gradient and low frequency static pressure fluctuations - design parameters previously reserved for larger aerodynamic or aero-acoustic wind tunnels. The aerodynamic design was achieved, in-part, by use of computational fluid dynamics and a purpose-built model wind tunnel.

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.

ISO 26262 is the actual standard for Functional Safety of automotive E/E (Electric/Electronic) systems. One of the challenges in the application of the standard is the distribution of safety related activities among the participants in the supply chain. In this paper, the concept of a Safety Element out of Context (SEooC) development will be analyzed showing its current problematic aspects and difficulties in implementing such an approach in a concrete typical automotive development flow with different participants (e.g. from OEM, tier 1 to semiconductor supplier) in the supply chain. The discussed aspects focus on the functional safety requirements of generic hardware and software development across the supply chain where the final integration of the developed element is not known at design time and therefore an assumption based mechanism shall be used.