Purely Ultracapacitor Energy Storage Closed-Loop Control HEV Model
Abstract: A purely ultracapacitor hybrid electric vehicle model with closed-loop control was developed for sizing components and optimizing control strategies. The vehicle components that were modeled included a purely ultracapacitor electrical energy storage unit, dc-dc converter, IC engine, automatic transmission and torque converter, standard road loads, and regenerative braking. A mean value engine model (MVEM) was developed for the IC engine. The torque converter was modeled based on an analogous electric motor model. Road loads included aerodynamic drag, rolling resistance, wheel bearing drag, and road grade. Vehicle acceleration was controlled with a PID control loop of the throttle and brake pedal with feedback from FTP drive cycles. The model operates in the time domain and provides real-time information on vehicle component performance as well as summative results such as total fuel economy and overall vehicle efficiency. Because the model is based on input signals from the pedal, algorithms developed in the software model can be directly applied to the hardware that controls the vehicle. The model was calibrated using conventional and hybrid electric vehicle parameters. Adjustments were made to match vehicle fuel economy, 0 to 60 mph acceleration, idle speed and torque, and aerodynamics. The model predicts city and highway fuel economy of 41.9 mpg and 35.8 mpg. This is over 37% higher than the conventional vehicle in city fuel economy without a loss in acceleration performance. The result is an accurate, detail oriented, vehicle model that can be used for engineering design as well as prototype development and hardware validation.


A Purely Ultracapacitor Energy Storage System for Hybrid Electric Vehicles Utilizing a Microcontroller Based dc-dc Boost Converter
Abstract: The design and testing of a purely ultracapacitor energy storage system for the improvement of hybrid electric vehicles is presented. The system utilizes two large ultracapacitor banks for energy storage and a dc-dc boost converter that is capable of supplying 8kW for voltage regulation. The system provides greater roundtrip efficiency over batteries, improves a vehicle's ability to recapture energy from regenerative braking, and is controlled and protected by a microcontroller. The paper presents design considerations, simulation, and hardware results of the system.


Optimized Solution Strategy for Solving Systems of Equations
Abstract: The focus of this paper is on the determination of an optimum solution strategy for solving linear and nonlinear systems of equations. The optimum solution strategy is determined by an algorithm we developed called Logical Equation Set Decomposition (LESD). LESD decomposes large systems into subsets of smaller systems. Our goal is to reduce the computational complexity of solving large equation sets by solving multiple smaller equation subsets. An occurrence matrix is used to optimize the number of subsets and the order of solution. Improved convergence rates were verified by integrating LESD into a standard numerical equation solver with a conventional Newton's method as the numerical engine. Linear and nonlinear equation sets were used to benchmark convergence rate. The results showed orders of magnitude reduction in computational time when using LESD for both the linear and nonlinear
equation sets.


Delivering a Hands-on Laboratory Using the Post Office, Internet,
and a Campus Visit
Abstract: We present the redesign of a sophomore-level mechanics of materials engineering laboratory course for distance delivery. The distance laboratory course combined multimedia computer experiments, portable hands-on exercises, and place-bound laboratory experiments. Class communication was accomplished through email, online discussion groups and telephone conversations. This new model in hands-on distance education provided valuable information that supports its effectiveness.


Eliminating the Forward/Backward Restriction in Vehicle Performance
and Energy Use Analysis
Abstract: The goal of this research was to develop and verify a computer analysis tool used for both vehicle simulation and design. Design analysis requires flexibility in setting up and solving the vehicle system of governing equations. Vehicle design analysis is fundamentally different from the structured modelling currently used in forward- or backward- facing vehicle simulation software. Unique numerical and equation management algorithms were developed to provide the flexibility and performance required for vehicle design analysis. These algorithms were combined into a software analysis tool called SmartDesigned Vehicles (SDV). Results from three different vehicle sizes and two different performance-based driving cycles were used to compare SDV with the Advanced Vehicle Simulator (ADVISOR) developed by the National Renewable Energy Laboratory. SDV was also validated with dynamometer test data. Results show that SDV predicts performance and energy use to within 5% of ADVISOR over most of the driving cycles. Additionally, SDV predicted vehicle performance to within 8% of dynamometer test data. SDV allows performance values as input and component size requirements as output. This result is a vehicle design tool that predicts component sizes based on performance, thereby enabling the engineer greater flexibility for design analysis.


Design and Evaluation of the University of Idaho Series Hybrid Future Truck
Abstract: The goals of the University of Idaho (UI) Team were to successfully design, install, and instrument a series hybrid electric powertrain in a General Motors (GM) Suburban for the Future Truck 2001 competition. Special efforts were made over the last year to centralize control and monitoring functions in a programmable logic controller (PLC). The UI-HEV was designed to meet or exceed the performance requirements as established by Future Truck 2001 Rules and Regulations. In addition, the UI Team raised $100,000 from various sponsors and participated in several community outreach events to raise public awareness for advanced vehicle technology. Based on modeling results, the UI Future Truck 2001 entry is predicted to achieve 50 mpg during typical city driving and 31 mpg for typical highway driving while maintaining emission levels under the stock Suburban equipped with a 1.9 liter
diesel engine.


A Logic-Based, Performance Driven Electric Vehicle Software Design Tool
Abstract: The goal of this project was to build a performance-driven steady-state hybrid electric vehicle design tool using novel equation management and solving routines currently under development at the University of Idaho. The uniqueness of this performance-driven model is in its logic and mathematics based design algorithms. These algorithms provide advantages when used with traditional numerical techniques. The design algorithms prevent singularity of sets of equations, thereby reducing the possibility of divergent solutions, while also giving added flexibility to the user in defining the system of equations and variables. The algorithms are also used to determine the most efficient solution path. This reduces the number of equations that must be solved simultaneously. Information is also provided to the user to help identify important component relationships. Based on the success of this project, these logic and numerical techniques could be integrated into ADVISOR's Autosize feature. The result would be a robust and flexible, performance-driven, hybrid electric vehicle component design and simulation software tool.