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Accurate characteristic prediction under constant power conditions can accurately evaluate the capacity of lithium-ion battery output. It can also ensure safe use for new-energy vehicles and electrochemical energy storage. As the battery voltage continues to drop under constant power conditions, the battery current output will accordingly increase, which brings a risk of thermal runaway in instances of weak heat dissipation. Therefore, knowing how to control the battery temperature is very critical for safe use. At present, the model-based method for characteristic prediction and temperature control has been used by most scholars, and that is also the key to this method. This work firstly extends a cell model to a pack-based electrochemical two-dimensional thermal coupling model, considering the heterogeneity of different cells inside the pack, and obtains the model parameters for a prismatic lithium-ion battery with a rated capacity of 42 Ah. Characteristic prediction under constant power conditions is then conducted based on an iterative solution method. Validations of characteristic prediction indicate the convenience of the developed models, with average absolute errors of voltage and temperature less than 36 mV and 0.4 K, respectively, and power error less than 0.005%. Finally, two model-based temperature feed-forward control strategies with lower cooling costs and shorter prediction times were developed based on the battery characteristic predictions, which leaves room for further controller development. Full article