This paper describes a systematic procedure, which includes analysis of strategy design criteria and development of real-time implementable strategy, to investigate the power management strategy for a range extended electric vehicle (RE-EV) using dynamic programming (DP). Since battery life is an important factor in replacement costs, battery energy losses are treated as one design criterion for battery protection. Fuel energy losses are another design criterion to address fuel economy. These two design criteria are expressed as two different cost functions for DP to evaluate both fuel-energy-loss-oriented and battery-energy-loss-oriented power management strategies. Considering driver comfort and battery life, limitations of noise, vibration, harshness, and battery charging/discharging currents are expressed as constraints in the DP process. Analysis results show that the fuel-energy-loss-oriented strategy can have better fuel economy, but its higher battery energy losses and average charging/discharging currents are unfavorable for battery life. On the contrary, battery-energy-loss-oriented strategy sacrifices some fuel economy in exchange for benefits to battery life. A rule-based, multi-mode switch strategy is then proposed as a power management strategy for RE-EV, which can require lower computation efforts. The proposed strategy employs a driving pattern recognition technique of switching among the control rule sets extracted from DP results of each representative driving pattern. Simulation results using three untrained driving patterns show that the proposed strategy improves the control performance of fuel economy and battery protection compared to that of conventional thermostat control strategy. (C) 2013 Elsevier Ltd. All rights reserved.