Homogeneous charge compression ignition (HCCI), a low temperature combustion (LTC) engine concepts, offers the potential to significantly reduce NOx and particulate, while also produce diesel-like efficiency. However, many technical challenges, including an established fuel performance metric, have hindered the advancement of this technology. In the present work, we used a design-of-experiments approach to address sensitivity of our previously-developed metric for LTC engine fuel performance: the LTC index. Using two different statistical strategies: one-at-a-time (OAT) analysis and 23 factorial design, we targeted driving cycle, weight, maximum power, as well as compression ratio as input parameters to determine their individual and interactive impacts to the LTC index for a wide range of fuels relevant to advanced internal combustion engines research. A detailed chemical mechanism, coupled with a validated Cantera-based HCCI engine model, was used to simulate the performance of these fuels. Separately, we performed driving cycle simulations by means of the advanced vehicle simulator (ADVISOR) package. Results showed significant decrease in the average LTC index when shifting over to a more aggressive-style, higher speed driving cycle, as opposed to that of an urban driving conditions. Additionally, it was shown that compression ratio and weight also exhibited significant impacts on the average LTC index, accounted for roughly 80% of total variation within our model.