Shared Control Based Energy Management Strategy for Hybrid Electric Vehicle Taking into Account Demand Power Optimization Vehicle Research Institute

Format:

Book

Conference/Event

Author/Creator:

Liu, Tao, author.

Contributor:

shi, Bingliang

Xie, Laiqing

Conference Name:

SAE Powertrains, Fuels & Lubricants Conference & Exhibition (2022-09-06 : Krakow, Poland)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

To further explore the potential of fuel economy for hybrid electric vehicle (HEV), a shared-control-based energy management strategy (SCEMS) with four modules of the human-vehicle closed-loop system, reference power calculation, driver power distribution, and shared control strategy is proposed. The SCEMS possesses three innovations. Firstly, the rational driver's power demand is considered to achieve optimal fuel consumption. Secondly, a dimensionality reduction strategy of two-dimension DP algorithm is proposed for online application. Finally, based on the shared control and the intelligent traffic system (ITS) a game mechanism between driver and controller is constructed to adapt to different driving styles and road conditions. In the human-vehicle closed-loop system, a model is built, combining the driver model with a longitudinal dynamic model, to optimize the power demand and power distribution. In the reference power calculation, the dynamic programming (DP) algorithm is utilized to produce the optimal power of a future forward road segment based on the ITS. The time complexity of DP algorithm is reduced by a state of charge (SOC) table looked up online derived from neural network and road condition identification. In the driver power distribution, the original demand power is assigned to the engine and motor. In the shared control strategy, two condition description equations are respectively constructed to indicate the fuel consumption rate of the engine and the efficiency of the motor, and then two adjustment curves are fitted to regulate the proportion of driver and controller to improve the power-wasting and ineffective behaviors. The problem of driving style and emergency road condition adaptation is settled depending on the cumulative-error-based weight adjustment strategy

Notes:

Vendor supplied data

Publisher Number:

2022-01-1122

Access Restriction:

Restricted for use by site license