This paper investigates the problem of path planning for manned eVTOL (electric Vertical Takeoff and Landing aircraft) in urban environments. Firstly, a three-dimensional urban space model is constructed using the hazard grid method. Considering the selected model of eVTOL, with range, operational risk, and altitude variation as objective functions, a path planning model for manned eVTOL with multiple constraints is developed, taking into account the characteristics of the aircraft and environmental limitations. Subsequently, an Improved Artificial Electric Field Algorithm (IAEFA) is proposed, which enhances the traditional Artificial Electric Field Algorithm (AEFA) by introducing an adaptive Coulomb parameter and incorporating a decreasing coefficient in the Coulomb constant calculation for simulation-based solution. Experimental results demonstrate that the constructed model achieves the expected outcomes. The solution effectiveness of path planning using the improved algorithm surpasses that of traditional Particle Swarm Optimization and Artificial Electric Field methods, resulting in shorter range, minimal altitude variation, and enhanced safety during operations. Finally, based on comparative experiments, the value of the decreasing coefficient is determined. The optimal solution effectiveness of the improved algorithm is achieved when the decreasing coefficient is set to 1.5.