This paper considers dealing with path constraints in the framework of the improved control vector iteration (CVI) approach. Two available ways for enforcing equality path constraints are presented, which can be directly incorporated into 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 the challenge, the l(1) penalty function and a novel smoothing technique are introduced, leading to a new effective approach. Moreover, on the basis of the relevant theorems, a numerical algorithm is proposed for nonlinear dynamic optimization problems with inequality path constraints. Results obtained from the classic batch reactor operation problem are in agreement with the literature reports, and the computational efficiency is also high.