The global optimization of hybrid systems described by linear time-varying ordinary differential equations is examined. A method to construct convex relaxations of general, nonlinear Bolza-type objective functions or constraints subject to an embedded hybrid system with explicit transitions is presented. The optimization problem can be solved using gradient-based algorithms in a branch and bound framework that is shown to be infinitely convergent when the implied state bounds are employed.