Cyber-Physical Energy-Saving Control for Hybrid Aircraft-Towing Tractor Based on Online Swarm Intelligent Programming

Zhou, Quan; Zhang, Yunfan; Li, Ziyang; Li, Ji; Xu, Hongming; Olatunbosun, Oluremi

doi:10.1109/tii.2017.2781230

Cited by 63 publications

(41 citation statements)

References 32 publications

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“…Research is underway to develop artificial intelligence (AI)-based engine calibration and control [159,160]. This development will move forward in three steps: (1) from manual calibration to AI-based calibration, (2) from map-based to model-based prediction control, and (3) from model-predictive control to model-free machine learning-based control.…”

Section: Discussionmentioning

confidence: 99%

Recent Progress in Automotive Gasoline Direct Injection Engine Technology

Shuai

et al. 2018

Automot. Innov.

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Gasoline direct injection (GDI) engines are currently the dominant powertrains for passenger cars. With the implementation of increasingly stringent fuel consumption and emission regulations worldwide, GDI engines are facing challenges owing to high particulate matter emissions and a tendency to knock, leading to a change in the research and design (R&D) issues compared with those in the twentieth century. This paper reviews the progress in research regarding GDI engine technologies over the past 20 years, focusing on combustion system configurations, and also highlights common issues in GDI R&D, including preignition and deto-knock, soot formation and PM emissions, injector deposits and gasoline compression ignition (GCI). First, an overview of recent developments in the field as driven by regulations is provided, following which progress in injection and combustion systems is examined. Third, the review addresses the occurrence and mechanism of deto-knock and considers means of suppressing this phenomenon. The fourth section discusses soot formation mechanisms and particulate matter emission characteristics of GDI engines and describes the application of gasoline particulate filter (GPF) after-treatment. The subsequent section summarizes studies regarding injector deposit formation, as well as pioneering research into GCI combustion modes. Finally, a summary and future prospects for GDI engine technologies are provided.

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Section: Discussionmentioning

confidence: 99%

Recent Progress in Automotive Gasoline Direct Injection Engine Technology

Shuai

et al. 2018

Automot. Innov.

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“…Moreover, this strategy is favored by its simplicity and ease of implementation. According to the CD-CS model defined in our previously published study [39], the engine torque demand, T e , is computed as a function of the engine speed, ω e , and the battery SoC as follows:…”

Section: Energy Management Strategymentioning

confidence: 99%

“…Different driving cycles 2, that determine the car-following behaviour; the variable, σ, in equation 9governs the torque (or power) split. Previous studies [34], [39] have given the recommended value, K base = [0.58, 0.10, 0.10], that is utilized as the baseline scheme in this work.…”

Section: Energy Management Strategymentioning

confidence: 99%

Multiobjective Co-Optimization of Cooperative Adaptive Cruise Control and Energy Management Strategy for PHEVs

Zhou

Makridis

et al. 2020

IEEE Trans. Transp. Electrific.

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Electrification, automation, and connectivity in the automotive and transport industries are gathering momentum, but there are escalating concerns over their need for co-optimization to improve energy efficiency, traffic safety, and ride comfort. Previous approaches to these multi-objective co-optimization problems often overlook trade-offs and scale differences between the objectives, resulting in misleading optimizations. To overcome these limitations, this study proposes a Pareto-based framework that demonstrably optimizes the system parameters of the cooperative adaptive cruise control (CACC) and the energy management strategy (EMS) for PHEVs. The high-level Pareto knowledge assists in finding a best-compromise solution. The results of this work suggest that the energy and the comfort targets are harmonious, but both conflict with the safety target. Validation using real-world driving data shows that the Pareto optimum for CACC and EMS systems, relative to the baseline, can reduce energy consumption (by 7.57 %) and tracking error (by 68.94 %), while simultaneously satisfying ride comfort needs. In contrast to the weighted-sum method, the proposed Pareto method can optimally balance and scale the multiple objective functions. In addition, sensitivity analysis proves that the vehicle reaction time impacts significantly on tracking safety, but its effect on energy saving is trivial.

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“…In this section, an intelligent power splitter is designed based on CAPSO algorithm, which has three main procedures, namely, initialization, main iteration, and optimal position retrieving. The details and principle of the CAPSO algorithm working procedure are discussed in the author's previous work in [11]. To solve the optimization problem in Eq.…”

Section: Intelligent Power Splitter and Doip Workflowmentioning

confidence: 99%

“…However, the performance of MPC is also determined by the precision of future velocity or power forecasts and its prediction model is hard formulated due to strong randomness and uncertainty [10]. The authors have proposed a real-time nonlinear model-based predictive energy management method, which makes it possible to carry on online nonlinear control optimization with advanced predictive models [11]. This research will develop advanced driver behaviour prediction methods to further improve the vehicle efficiency with online nonlinear model-based predictive control.…”

Section: Introductionmentioning

confidence: 99%

Cyber-Physical Energy-Saving Control for Hybrid Aircraft-Towing Tractor Based on Online Swarm Intelligent Programming

Cited by 63 publications

References 32 publications

Recent Progress in Automotive Gasoline Direct Injection Engine Technology

Recent Progress in Automotive Gasoline Direct Injection Engine Technology

Multiobjective Co-Optimization of Cooperative Adaptive Cruise Control and Energy Management Strategy for PHEVs

Dual-loop online intelligent programming for driver-oriented predict energy management of plug-in hybrid electric vehicles

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