This paper presents an optimized approach to planning energy-aware paths for skid-steer vehicles during elevation changes. Specifically, this work expands upon a previously presented power model by including the effect of elevation changes on the energy usage of the robot. The total power needed to travel to a goal location is then combined with an instantaneous center of rotation (ICR) kinematic model to plan energy-aware paths using a Sampling Based Model Predictive Optimization (SBMPO) algorithm. This method is demonstrated using a simulated environment with a wide range of varying scenarios representative of real-world usages. The results show that, in some hilly cases, it is more energy efficient to take a longer path when operating skid-steer robots on mixed terrain. These results are intended to improve the accuracy of energy consumption models for robotics.