Range Extension-Oriented Efficiency Optimization of Intelligent Electric Vehicle's Powertrain with Considering Multi Driving Constraints

The mileage anxiety problem is a critical issue for the intelligent electric vehicles. The efficiency optimization of in-telligent electric vehicle's powertrain by considering multi driving constraints is a promising solution to extend the driving range. In this paper, a range extension-oriented efficiency optimization (REEO) method, which consists of multi constraints construction, optimal efficiency searching, and optimal efficiency tracking control (OETC), is proposed for improving driving motor's efficiency and increasing driving range of intelligent electric vehicle. First, the vehicle dynamics model is built, and the multi driving constraints is constructed and mapped to the powertrain constraints through a cross domain collaboration (CDC) strategy. Second, the optimal efficiency of driving motor which subject to the multi constraints is searched by a recursive searching algorithm (RSA), and the driving motor is controlled by an OETC strategy. Third, the proposed REEO is validated by comparing with two state-of-the-art methods through a professional co-simulation platform consists of CarSim and Matlab. The validation results show the proposed method outperforms the state-of-the-art methods in extending the driving range of intelligent electric vehicles.