Condition Monitoring of Automotive Smart Systems utilizing Piezoresistive Stress Sensor Prof. Bongtae HAN (University of Maryland)
It is expected that advanced electronic components and smart systems would dictate the level of innovations in nearly all industrial sectors, including but not limited to automotive and other transport/logistics solutions, production equipment, energy and other infrastructure, etc. One such component is automotive electronic control unit (ECU), which controls the electrical system or subsystems in motor vehicles.
In a conventional ECU, a protective metal case is used to ensure reliability under harsh environmental conditions. Recently, an epoxy molding compound (EMC) was adopted to replace the metal case. The EMC technology reduced the manufacturing cost significantly, yet the presence of a large amount of outer EMC increased the stresses of ECUs during transfer molding process and operations (Gromala, Fischer, Zoller, Andreescu, Duerr, Rapp & Wilde, 2013, Kim, Han, Yadur & Gromala, 2014). The long-term reliability assessment of this newly adopted manufacturing technology should be conducted to make the technology a more viable alternative to various ECUs.
More recently, a silicon-based IForce piezoresistive stress sensor (Gromala, Fischer, Zoller, Andreescu, Duerr, Rapp & Wilde, 2013) was employed to assess the reliability of EMC-based advanced ECUs. In spite of serval advantages, most notably in-situ stress measurements during operations, the stress sensor provides only a local stress state around the sensor. It is inevitable, thus, to establish the relationship of the stresses between the stress sensor and the critical parts of ECUs such as solder joints, wire bonds, chips, etc., to be able to use the stress sensor in prognostics and health monitoring (PHM) systems.
Finite element analysis (FEA) has been used widely to predict the stresses and strains field inside the electronic devices, and it can be employed to develop the relationship. However, an accurate relationship can be obtained only when the FEA model is verified and calibrated until numerical predictions match to experimental data (Han, Guo, Lim & Caletka, 1996).
In this paper, a model/sensor hybrid approach was implemented to conduct failure prognostics of an automotive electronic control unit (ECU). A 3-D finite element model simulating a complex ECU was built, and its predictability was calibrated and verified by an optical displacement measurement technique called moiré interferometry.
The stress state of the ECU during thermal cyclic loadings are documented by piezoresistive-based stress sensors embedded in test vehicles. The silicon chip consists of two stress sensors, and it is packaged in a standard land grid array (LGA) package. In each sensor, there is a whole matrix of 12 sensing cells, being placed in a 4 × 4 array. Four cells in the corners are inactive.
The in-situ loading history was obtained using the data obtained from a stress sensor in conjunction with a numerical metric that converted the stress signal into in-situ temperature excursion. The verified model was then utilized to develop a quantitative relationship between the stress senor data and the stress of the most critical locations in the ECU.
The results demonstrated that the proposed approach (predictive modeling with a stress sensor) will be an effective way to conduct failure prognostics of ECUs subjected to various operating conditions.
Correlation of Physics-of-Failure to Stress-strain Curve for Quick-turn Monitoring of Solder Joint Reliability Dr. Yoonki SA (SEMES)
Physics-of-failure based reliability prediction technology is one of the key technologies in the field of prognostic and health management (PHM). In this study, physics of failure in solder interconnection is correlated with stress-strain curve obtained by die pull test to predict the joint quality and monitor the property change of solder bump within a reduced time period. Ball-grid-array (BGA) Si chip containing 6,000 solder bumps is used to demonstrate the validity of proposed method. With the conventional method using SEM analysis, it is very time-consuming to observe every single micro-bump and define each failure mode especially when IC includes a great number of solder bumps. The results indicate that it is possible to establish quick-turn monitoring methodology for the solder interconnection reliability and property change from the stress-strain curve of solder joints. Baseline strain-rate for ductile to brittle transition for reference joint of Sn-0.7Cu solder composition is investigated so that all the other deviations from the reference can be captured by using stress-strain relationship. In addition, it is found that failure mode in solder joint is correlated with stress-strain plot and therefore, joint reliability can be predicted without identifying the failure mode of the joints through SEM inspection. This study can provide the guideline for solder joint PHM from solder bump to chip system level.
A Study of the Degradation of Electronic Speed Controllers for Brushless DC Motors Mr. George GOROSPE, Chetan KULKARNI, Edward HOGGE, Andrew HSU and Natalie OWNBY (SGT Inc. at NASA Ames Research Center, Northrop Grumman Technical Services, NASA Postdoctoral Program at NASA Ames Research Center, Texas State University - San Marcos)
Brushless DC motors are frequently used in electric aircraft and other direct drive applications. As these motors are not actually direct current machines but synchronous alternating current machines; they are electrically commutated by a power inverter. The power inverter for brushless DC motors typically used in small scale UAVs is a semiconductor based electronic commutator that is external to the motor and is referred to as an electronic speed control (ESC). This paper examines the performance changes of a UAV electric propulsion system resulting from ESC degradation. ESC performance is evaluated on a new developed testbed featuring propulsion components from a reference UAV. An increase in the rise/fall times of the switched voltages is expected to cause timing issues at high motor speeds. This study paves the way for further development of diagnostic and prognostic methods for inverter circuits which are part of the overall electric UAV system.