The cycling industry is influenced by the approval of the tire pressure control system in competitive cycling. This system allows real-time adjustments to the tire-road interaction during races. The total rolling losses is the resistance resulting from tire-road interaction, incorporating resistance due to tire deformation and the dissipation of vibrational energy within the rider-bicycle system. This research investigates the influence of tire parameters on the total rolling losses during road cycling through three key measurements: ink print test, drum test, and rolling losses measurement. The ink print test captures the contact area between the tire and road surface under specified loads, revealing significant impacts of tire type, width, inflation pressure and vertical load on the contact patch shape. In addition, this study shows that an increase in contact patch measures is related to an increase in the rolling resistance coefficient (𝐶𝑟𝑟). The drum test extracts 𝐶𝑟𝑟 values related to pure rolling resistance by measuring the power needed to maintain constant velocity of a rotating drum when in contact with a loaded tire. Results indicate a significant influence of tire type, width, inflation pressure, vertical load and velocity on 𝐶𝑟𝑟 estimates. Combining 𝐶𝑟𝑟 obtain with drum testing with 𝐶𝑟𝑟 determined with total rolling losses measurements, provides insights into the contribution of vibrational losses to the total rolling losses. The study employs a novel bike trailer measurement technique to estimate total rolling losses, measuring the cyclist’s power while cycling at constant speed with elimination of aerodynamic drag. Despite some limitations, the bike trailer method successfully identifies optimal tire parameters for minimizing rolling losses on different road surfaces at varying speeds.

Commissioned for Team DSM, a computational model for professional road cycling races is developed to answer the question: ``What is the optimal cycling wheel-tire combination, available to Team DSM in order to ride different road cycling races as fast as possible?''. This model is used to make an approximation of the wind that the cyclist experiences, using race data from Team DSM. Using this wind approximation, race times for different wheel-tire combinations are compared. A sensitivity analysis of the model for the coefficient of rolling resistance, coefficient of drag multiplied with the frontal area, mass and rotational inertia is performed. Taking the error in the measurements of parameters into account, the sensitivity analysis and race time results both point to the ``C60 tubeless'' wheel-tire combination to be the fastest combination out of the available wheel-tire combinations to Team DSM. If the weight of a C36 wheel-set was reduced, this wheel set could outperform the C60 wheel-set on mountainous race courses.