To improve the overall fuel economy of e xtended-range electric vehicles and optimize battery usage，a hierarchical energy management strategy combining the advantages of model predictive control and fuzzy control was proposed to address the trade-off between real-time control and optimal performance in electric vehicle energy management.An energy flow model for an extended-range electric vehicle，consisting of a generator set，a hybrid energy storage system，and an electric motor，was developed.To optimize equivalent fuel consumption，optimal power allocation between the range extender and the hybrid energy storage system was determined through online rolling optimization using a model predictive controller.For the hybrid energy storage system，a fuzzy control strategy integrating variable speed intention was proposed to enhance battery protection.Simulation results show that，under urban driving cycle conditions，compared with traditional rule-based energy management strategies，the proposed hierarchical energy management strategy improves fuel economy by 11.23% and reduces battery power fluctuations by 44.4%.