Conjugate gradient method is widely used in many practical fields such as engineering problems，financial models and so on because of its simple iteration and low storage.For the largescale unconstrained optimization problems，a hybrid DLWYL conjugate gradient method is proposed—LHSDL method.It can be regarded as a modified DL conjugate gradient method，the first term of DL conjugate gradient method is modified by the conjugate parameter of WeiYaoLiu type conjugate gradient method which has good numerical and theoretical results.It can also be regarded as a modified WYL conjugate gradient method.By adding the second term of DL conjugate gradient method，the method may contain some Hessian information.The LHSDL method has a better property than DL method，i.e.，under the condition of strong Wolfe line search，it has sufficient descent property，and it is theoretically proved that LHSDL method has global convergence for general functions.Numerical experiments are carried out on a set of unconstrained optimization test problems of CUTEr collection.The performance profile of Dolan and Moré shows that LHSDL method is slightly superior to DK+method and MNVHS method.