Segemented Driving Cycle Based Optimization of Control Parameters for Power-Split Hybrid Electric Vehicle With Ultracapacitors

Xiaohua Zeng,Chen Cui,Dafeng Song,Guanghan Li,Yue Wang

doi:10.1109/access.2019.2926504

Xiaohua Zeng, Chen Cui + Show 3 more

Open Access

https://doi.org/10.1109/access.2019.2926504

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Abstract

As energy storage device of hybrid electric vehicles (HEVs), ultracapacitors feature the advantages of higher power density and longer life cycle compared with batteries. However, when ultracapacitors of the same power level are used instead of batteries, fuel consumption becomes more sensitive to changes in control parameters as ultracapacitors store much less energy, and the state of charge (SOC) is power-sensitive. In this paper, optimization of control parameters for a power-split HEV with ultracapacitors is addressed to achieve better fuel economy. First, a power-split HEV model and a corresponding control strategy are established under the MATLAB script environment for convenient analysis and application of an optimization algorithm. Second, focusing on the power-sensitive characteristic of the SOC, three key control parameters are determined, and their effects on fuel consumption are analyzed. Third, an improved particle swarm optimization (IPSO) algorithm is proposed to overcome the disadvantage of the PSO trapping into “local optimum” and improve optimization efficiency. To fully exploit the fuel-saving capability of the HEV, driving cycle segmentation is also considered. The IPSO is used to optimize three key control parameters under the segmented adapted world transient vehicle cycle. Finally, the optimal results are applied to hardware-in-the-loop test to verify the effectiveness of the proposed optimization method. Compared with the fuel consumption before optimization, the fuel saving rate reaches 9.20% in the urban section, 6.40% in the roadway section, and 5.40% in freeway section.

Highlights

Energy storage device is one of the core components of hybrid electric vehicles (HEVs) and electric vechicles (EVs)
Batteries are widely used as energy storage devices alone, whereas ultracapacitors are often used in combination with batteries[1], such successful applications have been achieved on urban EVs [2], [3]
This paper presents an algorithm to optimize the control parameters of power-split HEV equipped with ultracapacitors, aiming at reducing fuel consumption

Summary

INTRODUCTION

Energy storage device is one of the core components of HEVs and electric vechicles (EVs). In calibration of control strategy, the influence of control parameters on fuel economy is more notable than that of systems with batteries Given their low energy density, the ultracapacitors equipped in delivery trucks store low amounts of energy, and a little charging or discharging power can lead to a considerable change in SOC. To combine the models and optimization algorithm conveniently and enhance optimization speed, a power-split HEV model and a rule-based control strategy are established in the Matlab script environment On this basis, three control parameters affecting fuel consumption are obtained, which are basic engine charging power, limited regenerative braking power and the control target of SOC. (3) Based on the inherent defect of SPSO, a reasonably improved method is proposed, and better economy optimization results are obtained in the same iterations Considering their coupling relationship, the three control parametes are simultaneously optimized with IPSO.

MODELING BASED ON MATLAB SCRIPT

Findings

CONCLUSION