This paper considers dealing with path constraints within the framework of the improved control vector iteration (CVI) approach, for nonlinear dynamic optimization problems. Two available ways for enforcing equality path constraints are presented, which can be directly incorporated in the improved CVI approach. Inequality path constraints are much more difficult to deal with, even for small scale problems, because the time intervals where the inequality path constraints are active are unknown in advance. To overcome this challenge, the 1 l penalty function and a novel smoothing technique are introduced, leading to a new and effective approach. Moreover, on the basis of the relevant theorems, a numerical algorithm for nonlinear dynamic optimization problems with inequality path constraints is proposed. Results obtained from two classic cases are in agreement with the results reported in the open literatures, and the computational efficiency is also high.