PSU's Hardware-in-the-Loop Network

This project seeks to develop a first-of-its-kind campus-wide Hardware-in-the-Loop network at Penn State University. This network uses internet-enabled data-acquisition systems and local power-processing interfaces to connect vehicle subsystems - fuel cells, novel batteries, ultracapacitors, flywheel energy storage systems, high efficiency electric drive motors, advanced combustion engine test stands, and chassis dynamometers - in different laboratories distributed over the wide geographic area of the Penn State campus. These components can �talk� with each other just as they would interact in a vehicle, and thus enable the study of the coupled interaction of these components. Hence, researchers can better understand advanced Hybrid Electric Vehicle (HEV) architectures, components, simulation models, and energy management controllers without requiring construction of a new vehicle for each experiment and thus advance understanding of such architectures that are years or decades from integration.

The core challenge in developing a new HIL system is to solve issues of forming and operating a networked, embedded, distributed data-acquisition and control system where each node consists of a hardware or software representation of physical hardware. For most engineering systems, vehicles included, these nodes will often interact in a closed-loop manner such that unsupervised connectivity loss at each node may have catastrophic safety, cost, and data-quality implications. While other faculty are addressing the hardware platform deployments, our interest is to understand the influence of the node-to-node HIL communication interface including development and validation of low-order models of the hardware at each node. The HIL-specific challenges include finding communication sample rates and data lengths sufficient to maintain equivalence to true systems (Speed), finding scaling factors on the data such that one system can be correctly resized to interact with another (Scaling), and finding means to switch seamlessly between hardware and software representations such that there is no perceptible change in data (Switchover).

Investigators: Michael Petersheim, Dr. Joel Anstrom, Dr. Michael Lanagan, Dr. Andre Boehman, Jamie Clark, Kandler Smith, Dr. Dan Haworth, Ben Zile
Sponsors: Department of Energy, Advantech Inc. EAutomation Group, The MathWorks

Production Testing Techniques for Performance Assessment of the Primary Power and Starting System for Heavy Tactical Vehicles

This ongoing project is investigating advanced power management systems for a wide range of military heavy tactical vehicles, with primary focus on the Heavy Expanded Mobility Tactical Truck (HEMTT) power system. Due to excessive power demands during engine start, combined with harsh environmental conditions at areas of deployment, the battery system can have very limited life limiting the number of repeated start attempts or silent watch capability. To extend system reliability and longevity, advanced power management systems are being investigated that more closely integrate engine, battery, and power systems performance.

Investigators: Chris Rogran - Applied Research Lab, Dr. Joel Anstrom - PTI, Dr. S. Brennan - MNE/PTI, Ed Crow - Applied Research Lab, Karl Reichard - Applied Research Lab, Christian Hubicki
Sponsors: Department of Defense, Army TACOM

GPS-Free Terrain-Based Localization Using Vision Processing

GPS systems face severe hurdles for vehicle localization in the consumer market and military arenas. This can be verified by anyone who has tried to use on-vehicle GPS to measure their location within the urban canyons of big cities, or in the bottom lane of an elevated freeway, or in tight canyons, under forested canopies, or in poor weather. For millions of years, our ancestors kept track of their location and orientation without GPS; by looking at invariant features in far distance. The same method is used here as a means to estimate a vehicle's orientation in space. These estimates are important because several key chassis instabilities of a vehicle, namely sliding and rollover, require measurement or estimation of a vehicle's angular orientation in space.

Dr. S. Brennan and his research group at the Pennsylvania Transportation Institute are developing alternative vehicle measurement systems that use previously stored knowledge of the driving terrain. Like a blind person navigating through a complex world by constantly comparing a small set of cues to a recalled �map,� Brennan�s algorithms allow vehicles to similarly use stored knowledge of the driving environment to better interpret terrain-induced sensor cues and thereby extract vehicle position and orientation without GPS. Currently position estimates on the order of 10cm and orientation estimates within 0.2 degrees are being obtained in this research project via terrain-based cues alone. Ongoing work is integrating these measurements with existing GPS and INS position measurements.

Investigators: Vishi Gupta

GPS-Free Terrain-Based Localization Using Vehicle Disturbances

Have you ever been annoyed by the repetitive vibration in your vehicle caused by uneven paving in the highway? And if so, did you change lanes to find a smoother ride? Well, this might perturb you, but your vehicle might find this to be a vital clue to where you are located and where you are headed. In fact, your future vehicle might use this to locate itself with the same accuracy as GPS.

GPS navigation is becoming very common in today�s vehicles, however, poor reception, low satellite visibility, and the ease of jamming a GPS signal in battlefield operation has continued the interest in GPS-less navigation techniques. Also, GPS is not reliable enough for consumer vehicle automation. The Intelligent Vehicles and Systems research group has developed an algorithm that can localize a vehicle with sub-meter accuracy along the roadway simply by comparing a vehicle�s disturbance response with a terrain map, similar to maps stored on common �TomTom� devices. Having a redundant way of estimating vehicle position is an important step in advancing the state of the art vehicle automation and driver assist technology.

Investigators: Adam Dean

Terrain-Aware Robotics

Operation of autonomous mobile robots at speeds greater than a slow walk is challenged by the impact of terrain features on the dynamics and stability of the chassis. Vehicle-terrain interaction is especially detrimental to small tracked vehicles because it greatly increases the lateral sliding, which in turn can easily lead to tripped rollover, jumped track, and track mechanical failure. In order to control lateral slip, better understanding of this motion if first needed. Our group has been developing dynamic models to investigate the interaction of slip dynamics with chassis control of the vehicle, and how track-surface friction and terrain features (grade, superelevation) affects the system behavior. The goal is to develop dynamic models suitable for relatively high-speed (10-20 mph) off-road control of the vehicle, and to use these models to assist in the coordination of sensors and behaviors of groups of robots.

Investigators: Adam Dean

Experimental Testing of Mobile Robot Chassis Dynamics

Ground robots continue to increase in capability, including higher speeds to keep up with running or mounted humans, greater traction to negotiate ever harsher terrain, and greater lifting and payload capacity. As a result, stability analysis and consideration in robot chassis control is becoming particularly critical to prevent rollover and sideslip instabilities.

This project utilizes a rolling-roadway simulator to test robot chassis stability and control using a testing concept similar to an aircraft in a wind-tunnel: a pseudo-stationary vehicle is driven on a moving treadmill surface. An advantage of this system is that it allows testing at all speeds and configurations, enables advanced chassis controller tuning, and safely permits fault-testing. This system can operate as a stand-alone robot chassis tester, or as a hardware-in-the-loop system wherein subcomponents of the robot are tested individually while operating within a moving robot. Additionally, the surface can be wetted, tilted right/left at beyond 20 degrees, and/or tilted fore/aft at up to 6 degrees. The lateral motion in particular is useful to examine the robot behavior at the limits of adhesion or under sharp turning motions.

Investigators: Adam Dean

Sponsors: Department of the Navy (NavEOD)

Real-Time Terrain Mapping

Many safety-critical features near roadways are never surveyed after their construction, or are not resurveyed after geometric changes. These features include median geometries, locations of roadside or in-median barriers, shoulder drop-offs, rockfall faces, and offset distances to vegetation and other barrier-type geometries. Additionally, many roadways are poorly characterized geometrically including the vertical and horizontal curves, superelevation, and in some cases, even the location of the roadway itself!

This project is investigating the use of LIDAR laser-scanning techniques to extract roadway geometry features over very long segments of divided interstate highway (up to 6000 to 8000 miles across 5 to 6 states) with the intent to generate a database of major roadway features. This database will directly support an ongoing project on the influence of highway geometry on vehicle dynamics, and will also provide a valuable dataset for monitoring, visualization, and navigation in the future.

Investigators: Vishi Gupta, Adam Dean, Bridget Hamblin, Dr. Eric Donnell
Sponsors: National Academies, NCHRP 22-21 pooled fund in partnership with the Midwest Research Institute

FTA Reliability Correlation Between Test Track and In-Service Data

In 1987, the Federal Transit Administration (FTA) established a Bus Testing Program to comply with the Surface Transportation and Uniform Relocation Assistance Act (STURRA). STURRA mandated that all buses to be purchased with federal funds be tested and evaluated at a certified Bus Testing Facility. The Altoona Bus Research and Testing Center (ABRTC) in Altoona, Pennsylvania operates one such Bus Research and Test Facility in conjunction with the Pennsylvania Transportation Institute (PTI) at Penn State University. Since the first bus was tested in 1989, PTI has accumulated approximately 300 individual bus reports containing a myriad of data. To date ABRTC tests have identified more than 7100 malfunctions, resulting in numerous design changes.

In an effort to better generalize the data obtained at PTI�s test center, Penn State has begun a reliability analysis comparing the results of its Bus Testing Program to results obtained from transit agencies using bus models previously tested at PTI. The reliability analysis will focus on determining a relationship between the two sets of failure-data. The ultimate goal of the study is to produce a predictive failure model for all of PTI's tested bus models to include transit-specific performance factors such as climate, route harshness, number of miles on the bus per year, etc. Additionally, this study may motivate new reliability testing procedures, better correlation of chassis failures with experimental dynamic measures, and improved fault-tolerant analysis and design methods.

Investigators: Joe Yutko, Kshitij Jerath
Sponsors: The Federal Transit Agency