Elections employ various voting systems to determine winners based on voters' preferences. However, many recent ranked-choice elections have forced voters to truncate their ballots by only ranking a subset of the candidates. This study analyzes how forced ballot truncation affects the Bucklin, Coombs, plurality with runoff, and Schulze voting systems' abilities to output their true winning sets. This study also accounts for forced ballot truncation within the context of more realistic circumstances as compared to previous research on these voting methods including accounting for voters not completely filling out ballots and voters ordering their candidates who are aligned with their preferences instead of a random order. Using computer simulations, 840,000 sets of ballots were generated with a spatial model using different numbers of candidates, voters, and dimensions. The true winning set was determined for each system using complete preferences, then compared to winning sets derived from repeatedly truncated preferences within the same preference profile. Throughout the project, I will be working with Eric Pacuit, a professor at the University of Maryland, to consult on the design of the simulations as well as the process of analyzing the data. This project will result in an academic paper that will exhibit findings that provide insights into how forced ballot truncation impacts voting systems in realistic environments, hopefully aiding election designers in their work.