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Motion control of lane-change maneuvers under high-speed scenarios creates a great challenge for autonomous vehicles. However, a novel framework of lane-change trajectory planning and control based on the dynamic characteristics of distributed drive electric vehicles (DDEVs) is proposed in this paper to increase the possibility of safe driving in complex traffic conditions. First, a dilatational stability region determined by limits of stable yaw rate and saturated slip angles of each tire is employed to reveal dynamic instantaneous characteristics. On the basis of dilatational stability regions, the expanded envelopes by additional direct yaw moment can be identified by the expressions of irregular hexagons. Then, a series of unconstrained lane-change trajectory clusters can be generated to minimize longitudinal and lateral jerk, which is used to divide the global feasible region determined by the dilatational stability region and three-dimensional collision-free tunnel. Then, the technique for order preference for similarity to the ideal solution (TOPSIS) is utilized to achieve optimization of trajectory candidates from the global feasible region. The tracking controller aims at following the optimal lane-change trajectory, which is designed by the expanded stability boundaries of DDEV. Finally, simulations and experiments are conducted to validate the performance of the proposed planner and controller under high-speed, full-road and multi-vehicle traffic conditions.