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Following the Model-Based-Design (MBD) development process used presently by the automotive industry, the control systems for a new Series-Parallel Multiple-Regime Plug-in Hybrid Electric Vehicle (PHEV), UVic EcoCAR2, have been developed, implemented and tested. Concurrent simulation platforms were used to achieve different developmental goals, with a simplified system power loss model serving as the low-overhead control strategy optimization platform, and a high fidelity Software-in-Loop (SIL) model serving as the vehicle control development and testing platform. These two platforms were used to develop a strategy-independent controls development tool which will allow deployment of new strategies for the vehicle irrespective of energy management strategy particulars. A rule-based energy management strategy was applied and calibrated using genetic algorithm (GA) optimization. The concurrent modeling approach was validated by comparing the vehicle equivalent fuel consumption between the simplified and SIL models. An equivalency factor (EF) of 1 was used in accounting for battery state of charge (SOC) discrepancies at cycle end. A recursively-defined subsystem efficiency-based EF was also applied to try to capture real-world equivalency impacts. Aggregate results between the two test platforms showed translation of the optimization benefits though absolute results varied for some cycles. Accuracy improvements to the simplified model to better capture dynamic effects are recommended to improve the utility of the newly introduced vehicle control system development method. Additional future work in redefining operation modes and mode transition threshold conditions to approximate optimal vehicle operation is recommended and readily supported by the control system platform developed. / Graduate / 0540 / 0548 / 0790 / d.e.prescott@gmail.com

<p>Driveability analysis of terrain data offers an important technique for decision support for all kinds of movements in the terrain. The work described in this report uses a high resolution digital terrain model generated from the laser radar data and further processed by the Category Viewer program, and information from the Real Estate Map. Properties of features found in a filtering process are calculated and compared with a set of rules in a knowledge base to get a driveability cost. This cost is then visualized in a graphical user interface. </p><p>An evaluation of what driveability is and what it is affected by is performed, and a general cost function is developed, which can be used even if not all relevant information is available. </p><p>The methods for property and cost calculation need to be developed further, as well as the rules in the knowledge base. However, the implemented program offers a good framework for furtherresearch in the area.</p>

Driveability analysis of terrain data offers an important technique for decision support for all kinds of movements in the terrain. The work described in this report uses a high resolution digital terrain model generated from the laser radar data and further processed by the Category Viewer program, and information from the Real Estate Map. Properties of features found in a filtering process are calculated and compared with a set of rules in a knowledge base to get a driveability cost. This cost is then visualized in a graphical user interface. An evaluation of what driveability is and what it is affected by is performed, and a general cost function is developed, which can be used even if not all relevant information is available. The methods for property and cost calculation need to be developed further, as well as the rules in the knowledge base. However, the implemented program offers a good framework for furtherresearch in the area.