A comparative study of energy management systems under connected driving: cooperative car-following case

Ozan Yazar, Serdar Coskun, Fengqi Zhang, Lin Li

In this work, we propose connected energy management systems for a cooperative hybrid electric vehicle (HEV) platoon. To this end, cooperative driving scenarios are established under different car-following behavior models using connected and automated vehicles technology, leading to a cooperative cruise control system (CACC) that explores the energy-saving potentials of HEVs. As a real-time energy management control, an equivalent consumption minimization strategy (ECMS) is utilized, wherein global energy-saving is achieved to promote environment-friendly mobility. The HEVs cooperatively communicate and exchange state information and control decisions with each other by sixth-generation vehicle-to-everything (6G-V2X) communications. In this study, three different car-following behavior models are used: intelligent driver model (IDM), Gazis–Herman–Rothery (GHR) model, and optimal velocity model (OVM). Adopting cooperative driving of six Toyota Prius HEV platoon scenarios, simulations under New European Driving Cycle (NEDC), Worldwide Harmonized Light Vehicle Test Procedure (WLTP), and Highway Fuel Economy Test (HWFET), as well as human-in-the-loop (HIL) experiments, are carried out via MATLAB/Simulink/dSPACE for cooperative HEV platooning control via different car-following-linked-vehicle scenarios. The CACC-ECMS scheme is assessed for HEV energy management via 6G-V2X broadcasting, and it is found that the proposed strategy exhibits improvements in vehicular driving performance. The IDM-based CACC-ECMS is an energy-efficient strategy for the platoon that saves: (i) 8.29% fuel compared to the GHR-based CACC-ECMS and 10.47% fuel compared to the OVM-based CACC-ECMS under NEDC; (ii) 7.47% fuel compared to the GHR-based CACC-ECMS and 11% fuel compared to the OVM-based CACC-ECMS under WLTP; (iii) 3.62% fuel compared to the GHR-based CACC-ECMS and 4.22% fuel compared to the OVM-based CACC-ECMS under HWFET; and (iv) 11.05% fuel compared to the GHR-based CACC-ECMS and 18.26% fuel compared to the OVM-based CACC-ECMS under HIL.

在這項(xiàng)工作中，作者提出了用于協(xié)作式混合動(dòng)力電動(dòng)汽車 (HEV) 排的互聯(lián)能源管理系統(tǒng)。為此，利用互聯(lián)和自動(dòng)駕駛汽車技術(shù)，在不同的跟車行為模型下建立協(xié)同駕駛場(chǎng)景，從而開發(fā)出探索混合動(dòng)力汽車節(jié)能潛力的協(xié)同巡航控制系統(tǒng)（CACC）。作為實(shí)時(shí)能源管理控制，采用等效消耗最小化策略（ECMS），實(shí)現(xiàn)全球節(jié)能，促進(jìn)環(huán)保出行。HEV 通過(guò)第六代車聯(lián)網(wǎng) (6G-V2X) 通信相互協(xié)作通信和交換狀態(tài)信息和控制決策。在這項(xiàng)研究中，使用了三種不同的跟車行為模型：智能駕駛員模型（IDM），Gazis-Herman-Rothery (GHR) 模型和最佳速度模型 (OVM)。采用豐田普銳斯HEV六排場(chǎng)景協(xié)同駕駛、新歐洲駕駛循環(huán)（NEDC）、全球統(tǒng)一輕型車輛測(cè)試程序（WLTP）和高速公路燃油經(jīng)濟(jì)性測(cè)試（HWFET）下的模擬，以及人在環(huán)(HIL) 實(shí)驗(yàn)是通過(guò) MATLAB/Simulink/dSPACE 進(jìn)行的，用于通過(guò)不同的跟馳鏈接車輛場(chǎng)景進(jìn)行協(xié)作 HEV 隊(duì)列控制。