According to the parameters of a pure electric SUV equipped with a CVT(continuously variable transmission) gearbox, this paper matches the parameters of the drive motor, drive battery, and transmission system. According to the matching parameters, AVL Cruise software was used to model the entire vehicle, and the power and economy of the vehicle were analyzed. The simulation results demonstrated that the matching outcomes satisfied the needs for both power and economics. In order to further improve the economy of pure electric vehicles, the vehicle model is optimized with the final ratio of the vehicle as the optimization parameter and the power consumption per 100 kilometers under NEDC operating conditions as the objective function. On the premise that the power performance meets the requirements, the optimization results show that before and after optimization, the power consumption per 100 Km under NDEC (new European driving cycle) operating conditions is reduced by 1.02KWh, a reduction of 6.01%, and the power consumption per 100 kilometers under WLTP(world light vehicle test procedure) operating conditions is reduced by 0.91KWh, a reduction of 4.97%.
In order to improve the chart recognition speed and the recognition success rate of the large field-of-view high-sensitivity star sensitizer, an improved artificial bee colony algorithm combined with the three anti-perturbation parameters is proposed as a chart recognition method. The method is based on the improved artificial bee colony algorithm to find the optimal paths for all the stars in the main star feature region; then, the optimal path length is used to find addresses in the navigation feature library, and the interstellar angular distances of the first three navigation stars in the optimal paths, d12/d23 , are taken as the main recognition features for matching and identification; finally, the three perturbation parameters are taken as the auxiliary recognition features to reduce the redundancy of the matching and to serve as a validation of the recognition.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.