An accurate control-oriented electrothermal model is of great importance for onboard temperature monitoring and efficient performance management of lithium (Li)-ion batteries in automobile applications. This article presents a control-oriented electrothermal model for pouch-type electric vehicle batteries. This model uses the Chebyshev–Galerkin (CG) approximation method and captures the heat generation of positive and negative tabs, the heat flow between the tabs and the body, and the uneven heat generation inside the battery. This model consists of two lumped-mass submodels for positive and negative tabs and a 2-D CG submodel for the main battery body. The heat generation in the 2-D CG model is strongly dependent on the electrical parameters that are conversely functions of battery temperature. The lumped-mass models are decoupled from the 2-D CG model and parameterized separately by the particle swarm optimization algorithm and validated against the temperature measurements (covering three test scenarios) of a 20-Ah pouch-type Li-ion iron phosphate battery. The results demonstrate that the coupled model accurately predicts the temperatures of the tabs and the temperature distribution inside the battery. Besides, the computational complexity of the coupled model is also evaluated, and the result shows that the model has great potential for real-time temperature monitoring and efficient thermal management.