ABSTRACT The drive range of electric vehicle (EV) is one of the major limitations that impedes its universalism. A great deal of research has been devoted to drive range improvement of EV, an accurate and efficiency energy consumption estimation plays a crucial role in these researches. However, the majority of EV’s energy consumption estimation models are based on single motor EV, these models are not suitable for dual-motor EVs, which are composed of more complex transmission mechanisms and multiple operating modes. Thus, an energy consumption estimation model for dual-motor EV is proposed to estimate battery power. This article focuses on studying the operating modes and system efficiency in each operating mode. The limitation of working area of each mode ensures the vehicle dynamic performance, then PSO algorithm is adopted to optimize the torque (speed) distribution between two motors to improve the system efficiency in the coupled driving mode. Finally, the energy consumption estimation model is established by multiple linear regression (MLR). The result shows that the proposed model has a high precision in energy consumption estimation of dual-motor EV. 相似文献
The characteristics of colloids in urban road runoff with different traffic in Beijing, China, such as concentration, particle size, chemical property, and affinity for heavy metals were determined. The concentration of colloids was high, and an evident first flush effect was found in the runoff of road with heavy traffic. A large portion of colloids were distributed in the range of 1–10 μm. Traffic activity, rainfall intensity, and time of sample collection would not change the size distribution of colloids in the road runoff. The chemical property of colloids in the road runoff would be influenced by the soil erosion nearby green space, causing the content of organic colloids was high. The correlation coefficient between the concentration of colloids in colloidal fractions and the concentration of heavy metals (Cu, Zn, Cd, Pb, Fe, and Mn) in the road runoff with different traffic decreased with the same sequence from 0.02–0.2 μm, 0.2–0.45 μm, 0.45–1 μm, to 1–10 μm, suggesting that the heavy metals had stronger affinity for the colloids with small size. The concentration of Cu, Pb, and Zn exhibited significant correlations with the concentration of organic colloids in the road runoff. More aggregated spherical particles were found in the TEM image of the road runoff with heavy traffic. Zeta potentials and RMV data showed that the colloids with smaller size and the colloids in the road runoff with lighter traffic were much more stable.