This I-Corps project proposes to further develop a technology for traffic signal management in transportation systems. This technology has been evolving through various research projects since 2002. The proposed technology provides a solution to meet demands for efficiency, scalability, security and robustness in the control and management of large-scale time-sensitive industrial applications. It has been founded on cooperative distributed control technologies and is capable of addressing the network-in-the-loop challenges, such as time delay, packet loss and bandwidth allocation, efficiently. It can effectively integrate distributed sensors, distributed actuators, distributed controllers, and communication networks to make intelligent decisions over a physically and/or virtually connected space. This space can be as small as a room or a building, or can be as big as a community, or even a city. Compared to the centralized counterpart, the proposed technology does not rely on a specialized control center but a group of distributed smart control modules which make intelligent decisions by exchanging information with local neighbors. It scales well as the network grows with plug-and-play capabilities, exhibits resilience to the communication delays and robustness to node and link failures.

This technology is a platform technology that meets the critical needs of many industrial applications, such as: 1) traffic signal management in intelligent transportation systems, 2) energy management in building management systems, 3) electric vehicle charging strategies in a municipal parking deck or a community environment, 4) mobile devices power management in an aggregate level. Further development of this technology will impact all of these areas and facilitate the transition trend from centralized control to distributed control, which may bring about significant advances in the corresponding hardware and software development for industrial control systems.

Project Report

The Electric Vehicle (EV) adoption rate remains low in the US (3.38 % of new cars were EVs in 2012) because of the anxiety felt by many drivers about the remaining driving range of their vehicles. Existing technologies in the EV market do not provide high enough range estimation accuracy. This Innovation Corps project has tested the commercial feasibility of a Smart Battery Gauge technology that provides accurate battery level and driving range information to alleviate the drivers’ range anxiety. A technology prototype is developed to demonstrate its three salient features outperforming the existing solutions: 1) Accurate battery charge level estimation using the adaptive battery model parameters; 2) Accurate EV remaining driving range prediction using big data analytics; 3) Cost-effective development using configurable battery model. During the project, 4 invention disclosures related to the Smart Battery Gauge technology have been submitted to the Office of Technology Transfer (OTT) of North Carolina State University, resulting in two pending U.S. patents. Harrison Analytic Technology (HAT), LLC, a spin-off from NCSU composed of technical founding members and experienced business consultants, was incorporated to carry out the technology commercialization with the exclusive license of the patent-protected IP. HAT has been awarded its first grant Daugherty Endowment for the initial start-up expense in 2013. HAT has also applied for NSF Small Business Innovation Research (SBIR) Phase I grant and Accelerating Innovation Research: Technology Transfer (AIR: TT) grant for future commercialization funds. The project has fostered a cooperative relationship between NCSU and several industry partners, such as Organic Transit Co., Samsung Advanced Institute of Technology, and Ford Motor Company. The prototype of the Smart Battery Gauge technology has been evaluating by these EV market strategy partners and potential customers. Three graduate students have also participated in the summer intern program of these companies in 2013 and 2014.

Agency
National Science Foundation (NSF)
Institute
Division of Industrial Innovation and Partnerships (IIP)
Type
Standard Grant (Standard)
Application #
1338371
Program Officer
Rathindra DasGupta
Project Start
Project End
Budget Start
2013-04-15
Budget End
2014-09-30
Support Year
Fiscal Year
2013
Total Cost
$50,000
Indirect Cost
Name
North Carolina State University Raleigh
Department
Type
DUNS #
City
Raleigh
State
NC
Country
United States
Zip Code
27695