Increasing fuel efficiency and reducing environmentally unfriendly exhaust
emissions are two major, ongoing goals of the automotive industry – goals
which can be achieved by attaining the proper mix of oxygen and fuel. The next
generation of automotive engines will use wide-range oxygen sensors, which can
determine how rich or lean the air/fuel (A/F) ratio is and help to regulate
clean, efficient motor operation. Delphi Corporation, a world leader in mobile
electronics and transportation components located in Troy, Michigan, chose ALGOR
FEA software to thermally optimize a wide-range oxygen sensor. "I selected
ALGOR because it is a complete package with CAD support, meshing and easy-to-use
analysis tools," said Senior Project Engineer C. Scott Nelson, who
optimized the sensor design.
Better Sensors for Better Fuel Efficiency
Oxygen sensors have been used in automotive exhaust systems for over 25
years. To date, the type of sensor used, called a switching oxygen sensor, can
only determine whether the A/F ratio is rich (excess fuel) or lean (excess
oxygen). Replacing switching oxygen sensors with wide-range oxygen sensors is
one of the technologies that is contributing to the development of lean burn
engines, which lets the engine burn less fuel under low pressure demand, but
increases intake to admit more fuel when needed, such as during acceleration.
Burning less fuel contributes to fuel efficiency while lower emissions result
from the fuel combusting more completely.
The initial (left) and final (right) designs for the wide-range oxygen sensor.
In designing any exhaust sensor, thermal optimization is critical due to the
extreme operating conditions from -40°C to over 1000°C. Durable,
cost-effective materials and maintaining a short overall sensor length are also
important design considerations. Important sensor components such as the
terminal and seal are typically made of materials that can break down over time
if the temperature of the sensor is not controlled. Although increasing the size
of a part is an easy way to reduce the temperature, shorter sensors experience
less potentially destructive vibration than longer ones. In addition, auto
manufacturers prefer shorter sensors because they are easier to integrate into
exhaust designs and easier to install.
FEA-Based Thermal Optimization
To thermally optimize the sensor, Nelson worked with a 2-D axisymmetric
cross-section of the sensor. The thermal loads and constraints represented worst
case conditions of 1000°C exhaust temperature, 150°C ambient temperature and
free convection (no air current). These conditions were simulated using a
combination of convection, conduction and radiation loads.
The wide-range oxygen sensor was modeled in using a 2-D axisymmetric cross-section (lower right). The ALGOR heat transfer analysis results of the final design are shown above (upper left).
Over the course of dozens of analyses, Nelson optimized the geometry and
material properties of the sensor components. The strategies behind the design
changes were to restrict vertical heat flow, promote radial heat flow and
increase heat flow through the components. In some cases, he even experimented
with different materials having different thermal conductivity properties
without having a particular material in mind and then researched materials that
had similar properties.
"Using ALGOR, I was able to reduce the temperature at two critical
locations in the sensor by 20% which kept the peak temperatures below the
material's maximum threshold; this greatly improved sensor durability and
robustness," said Nelson.
Laboratory tests using a dynamometer correlated well with the FEA results
"My results correlated to laboratory results within 4%," said
Nelson. "I'm very satisfied with this correlation, especially since the
variables of an experiment can never be controlled as well in the laboratory as
they can be with an FEA model. Still air is especially difficult to replicate
experimentally; even a small amount of air flow can significantly affect the
results."
This thermal optimization was not only Nelson's first project using FEA, but
a departure from the way he has designed products in the past. "Iteratively
analyzing designs and optimizing both the geometry and the materials used helped
me to develop a much better design than I could have achieved without those
virtual 'hands-on' results," said Nelson. "As a product designer, I
find that performing my own analyses leads to a much more interactive and
informed design process. It saves tens of thousands of dollars over iterative
prototype testing and, with a simple model like this one, I can do far more
iterations than would be logistically feasible if I turned the analysis work
over to someone else."
The completed sensor design is currently being integrated into the next
generation of automotive engines, which are expected to be used in 2004.
C. Scott Nelson is a Senior Project Engineer for Delphi Corporation. He holds
a BSME from Lawrence Technological University and a MSE from Purdue
University.
C. Scott Nelson of Delphi Corporation used ALGOR software to optimize a wide-range oxygen sensor that will help automobiles to run more cleanly and efficiently.
Delphi Corporation is a world leader in mobile electronics and transportation
components and systems. Headquartered in Troy, Michigan, Delphi supplies major
automotive manufacturers as well as providing aftermarket automotive parts.
