This study analyzed the effect of lane-changing behavior on traffic flow emissions and energy consumption of road sections in fuel vehicle-battery electric vehicle (FV-BEV) and human-driven vehicle-cooperative adaptive cruise control (HDV-CACC) multi-dimensional mixed traffic flow environments. Based on the traditional energy consumption model, a multi-dimensional mixed traffic flow energy consumption model was established by considering the BEV and CACC penetration rates. The microscopic traffic flow theory approach was used to analyze lane-changing behavior and the influencing mechanism of lane-changing behavior on the energy consumption of multi-dimensional mixed traffic flow, and MATLAB was used for the experimental simulation. The lane-changing behavior of the leading vehicle had a negative impact on the energy consumption of road segment traffic flow. Within the 95% effective impact range, the average energy consumption of traffic flow with respect to lane-changing behavior was 7.8% higher than that of the following traffic flow. The BEV penetration rate was beneficial for reducing the energy consumption of mixed traffic flow. At an economic velocity, the energy consumption of homogeneous BEV traffic flow was only 58.3% of that of homogeneous FV traffic flow. The CACC penetration rate could increase the traffic flow toughness. When the BEV penetration rate was constant, the higher the CACC penetration rate, the smaller the impact of lane-changing behavior on emissions. When traffic flow was completely transformed to homogeneous CACC traffic flow, lane-changing behavior only increased the overall energy consumption of the traffic flow by 4.99%, which was lower than the average level. Consequently, the promotion of BEV and CACC can improve the impact of traffic emissions on air pollution. When CACC penetration is low, reducing unnecessary lane-changing behavior to ensure the stability of traffic flow is also an effective way to reduce emissions.Implications: Multi-dimensional mixed traffic flow energy consumption model is proposed.CACC penetration rate, BEV penetration rate and lane-changing behavior will change traffic energy consumption. In this paper, different influencing factors are analyzed one by one.It provides a theoretical basis for relevant departments of traffic management to optimize vehicle emissions and traffic organization.