Control Engineering Practice最新文献_第3页

Optimization of the energy-comfort trade-off of HVAC systems in electric city buses based on a steady-state model 基于稳态模型的城市电动公交车暖通空调系统能源-舒适性权衡优化研究

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-13 DOI: 10.1016/j.conengprac.2024.106158

Fabio Widmer, Stijn van Dooren, Christopher H. Onder

The electrification of public transport vehicles offers the potential to relieve city centers of pollutant and noise emissions. Furthermore, electric buses have lower life-cycle greenhouse gas (GHG) emissions than diesel buses, particularly when operated with sustainably produced electricity. However, the heating, ventilation, and air-conditioning (HVAC) system can consume a significant amount of energy, thus limiting the achievable driving range. In this paper, we address the HVAC system in an electric city bus by analyzing the trade-off between the energy consumption and the thermal comfort of the passengers. We do this by developing a dynamic thermal model for the bus, which we simplify by considering it to be in steady state. We introduce a method that is able to quickly optimize the steady-state HVAC system inputs for a large number of samples representative of a year-round operation. A comparison between the results from the steady-state optimization approach and a dynamic simulation reveals small deviations in both the HVAC system power demand and achieved thermal comfort. Thus, the approximation of the system performance with a steady-state model is justified. We present two case studies to demonstrate the practical relevance of the approach. First, we show how the method can be used to compare different HVAC system designs based on a year-round performance evaluation. Second, we show how the method can be used to extract setpoints for online controllers that achieve close-to-optimal performance without any predictive information. In conclusion, this study shows that a steady-state analysis of the HVAC systems of an electric city bus is a valuable approach to evaluate and optimize its performance.

公共交通车辆的电气化为缓解城市中心的污染物和噪音排放提供了可能。此外，电动公交车的生命周期温室气体排放量低于柴油公交车，尤其是在使用可持续生产的电力的情况下。然而，加热、通风和空调（HVAC）系统会消耗大量能源，从而限制了可实现的行驶里程。在本文中，我们通过分析能源消耗和乘客热舒适度之间的权衡来解决电动城市公交车中的暖通空调系统问题。为此，我们为公交车开发了一个动态热模型，并将其简化为稳态模型。我们引入了一种方法，能够快速优化全年运行的大量样本的稳态暖通空调系统输入。通过比较稳态优化方法和动态模拟的结果，可以发现暖通空调系统的电力需求和达到的热舒适度都存在较小的偏差。因此，用稳态模型近似计算系统性能是合理的。我们介绍了两个案例研究，以证明该方法的实用性。首先，我们展示了如何使用该方法在全年性能评估的基础上比较不同的暖通空调系统设计。其次，我们展示了该方法如何用于提取在线控制器的设定点，从而在没有任何预测信息的情况下实现接近最优的性能。总之，本研究表明，对电动城市公交车的暖通空调系统进行稳态分析，是评估和优化其性能的重要方法。

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引用次数: 0

Sliding-mode energy management strategy for dual-source electric vehicles handling battery rate of change of current 处理电池电流变化率的双源电动汽车滑动模式能量管理策略

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-13 DOI: 10.1016/j.conengprac.2024.106157

Hai-Nam Nguyen , Bảo-Huy Nguyễn , Thanh Vo-Duy , João Pedro F. Trovão , Minh C. Ta

For years, developing energy management strategies (EMS) for hybrid energy storage systems (HESS) of electric vehicles (EV) has been a topic of great interest thanks to the mutual support of energy sources. In this paper, we approach the energy management problems from the control point of view to exploit the remarkable advantages of control techniques in treating state constraints, system stability, and optimality. By that, we propose a sliding-mode strategy for the EMS of the battery–supercapacitor HESS on EVs. In order to prolong the lifespan of the battery, the rate of change in battery reference current is directly handled as the control input of the management system which is, to our best knowledge, novel in literature. Control parameters of the proposed EMS are optimally tuned by using Particle Swarm Optimization. The performance of the proposed EMS is validated by off-line simulation as well as real-time experiments on a Signal Hardware-in-the-Loop system with various comparisons, testing scenarios, and quality indices. The results and the approach of the paper illustrate the effectiveness and feasibility of the management system that can be applied not only to EVs but also to larger-scale energy networks in further research.

多年来，由于能源的相互支持，为电动汽车（EV）的混合储能系统（HESS）开发能源管理策略（EMS）一直是一个备受关注的话题。在本文中，我们从控制的角度来探讨能源管理问题，以利用控制技术在处理状态约束、系统稳定性和最优性方面的显著优势。为此，我们提出了一种用于电动汽车电池-超级电容器 HESS 的 EMS 滑动模式策略。为了延长电池的使用寿命，我们直接将电池参考电流的变化率作为管理系统的控制输入进行处理，据我们所知，这在文献中尚属首次。利用粒子群优化技术对所提出的 EMS 的控制参数进行了优化调整。通过离线仿真以及在信号硬件在环系统上的实时实验，对所提出的 EMS 的性能进行了验证，并进行了各种比较、测试场景和质量指标。本文的结果和方法说明了管理系统的有效性和可行性，不仅可应用于电动汽车，还可在进一步研究中应用于更大规模的能源网络。

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引用次数: 0

Enhancing truck platooning efficiency and safety—A distributed Model Predictive Control approach for lane-changing manoeuvres 提高卡车编队效率和安全性--变道机动的分布式模型预测控制方法

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-12 DOI: 10.1016/j.conengprac.2024.106153

Beatriz Lourenço , Daniel Silvestre

The advent of autonomous driving technologies has paved the way for notable advancements in the realm of transportation systems. This paper explores the dynamic field of truck platooning, focusing on the development of a Nonlinear Model Predictive Control (NMPC) approach within a Cooperative Adaptive Cruise Control (CACC) framework. The research tackles the critical challenges in obstacle avoidance and lane-changing manoeuvres. The core contribution of this work lies in the development and implementation of a novel NMPC algorithm tailored to platoon control. This framework integrates a penalty soft constraint to guarantee obstacle avoidance and maintain platoon coherence while optimising control inputs in real-time. Several experiments, including static and dynamic obstacle avoidance scenarios, validate the efficacy of the proposed approach. In all experiments, the vehicles closely follow one another, resulting in smooth trajectories for all system states and control input signals. Even in the event of abrupt braking by the ego vehicle, the platoon remains cohesive. Moreover, the proposed NMPC proves to be computationally efficient when compared to the state-of-the-art.

自动驾驶技术的出现为交通系统领域的显著进步铺平了道路。本文探讨了卡车排队行驶的动态领域，重点是在合作自适应巡航控制（CACC）框架内开发非线性模型预测控制（NMPC）方法。该研究解决了避障和变道操纵中的关键难题。这项工作的核心贡献在于开发和实施了一种专为排队控制量身定制的新型 NMPC 算法。该框架集成了惩罚软约束，以保证避障和保持排的一致性，同时实时优化控制输入。包括静态和动态避障场景在内的多项实验验证了所提方法的有效性。在所有实验中，车辆都紧紧相随，从而在所有系统状态和控制输入信号下都能获得平滑的轨迹。即使在 "自我 "车辆突然制动的情况下，车队仍能保持凝聚力。此外，事实证明，与最先进的方法相比，所提出的 NMPC 具有很高的计算效率。

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引用次数: 0

Nonlinear model predictive control with set terminal constraint for safe robot motion planning via speed and separation monitoring 非线性模型预测控制与设定终端约束，通过速度和分离监控实现安全的机器人运动规划

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-08 DOI: 10.1016/j.conengprac.2024.106155

Aigerim Nurbayeva, Matteo Rubagotti

This paper proposes a methodology for safely planning the motion of a robot manipulator sharing its workspace with a human operator. The motion of the robot is continuously re-planned via nonlinear model predictive control (NMPC), imposing the so-called speed and separation monitoring (SSM) condition to guarantee human safety. Contrary to previous works in the field, the NMPC algorithm is designed with an ellipsoidal terminal constraint, to enlarge the domain of attraction compared to the case in which a point terminal constraint was imposed. This is a very important aspect in real-world applications, allowing the robot to plan its motion from initial configurations that are relatively far from the goal point. Theoretical results are proved on recursive feasibility and closed-loop stability for both cases of NMPC with point and set terminal constraints, under the simplifying assumption of a static human. The effectiveness of the proposed approach is verified via numerical evaluation of the domain of attraction and with experiments on a UR5 manipulator.

本文提出了一种方法，用于安全规划与人类操作员共享工作空间的机器人机械手的运动。通过非线性模型预测控制（NMPC）不断重新规划机器人的运动，并施加所谓的速度和分离监控（SSM）条件，以确保人类安全。与该领域以前的工作不同，NMPC 算法设计了一个椭圆形终端约束，与施加点终端约束的情况相比，扩大了吸引域。这在实际应用中是非常重要的，它允许机器人从离目标点相对较远的初始配置开始规划运动。在人类静态的简化假设下，证明了带有点和集合终端约束的 NMPC 两种情况下的递归可行性和闭环稳定性的理论结果。通过对吸引域进行数值评估以及在 UR5 机械手上进行实验，验证了所提方法的有效性。

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引用次数: 0

Randomized iterative feedback tuning for fast MIMO feedback design of a mechatronic system 随机迭代反馈调整用于机电一体化系统的快速 MIMO 反馈设计

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-06 DOI: 10.1016/j.conengprac.2024.106152

Leontine Aarnoudse , Peter den Toom , Tom Oomen

Iterative feedback tuning (IFT) enables the tuning of feedback controllers using only measured data to obtain the gradient of a cost criterion. The aim of this paper is to reduce the required number of experiments for MIMO IFT. It is shown that, through a randomization technique, an unbiased gradient estimate can be obtained from a single dedicated experiment, regardless of the size of the MIMO system. The gradient estimate is used in a stochastic gradient descent algorithm. The approach is experimentally validated on a mechatronic system, showing a significantly reduced number of experiments compared to standard IFT.

迭代反馈调谐（IFT）可以仅使用测量数据来获得成本准则的梯度，从而对反馈控制器进行调谐。本文旨在减少 MIMO IFT 所需的实验次数。研究表明，通过随机化技术，无论多输入多输出系统的规模如何，都能从一次专门实验中获得无偏梯度估计值。梯度估计值用于随机梯度下降算法。该方法在机电一体化系统上进行了实验验证，结果表明，与标准 IFT 相比，实验次数大大减少。

引用次数: 0

Control design and analysis for autonomous underwater vehicles using integral quadratic constraints 使用积分二次约束的自主式水下航行器控制设计与分析

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-05 DOI: 10.1016/j.conengprac.2024.106142

Sourav Sinha , Mazen Farhood , Daniel J. Stilwell

This paper addresses the design and analysis of path-following controllers for an autonomous underwater vehicle (AUV) using a robustness analysis framework based on integral quadratic constraints (IQCs). The AUV is modeled as a linear fractional transformation (LFT) on uncertainties and is affected by exogenous inputs such as measurement noise and ocean currents. The proposed approach leverages a learning-based method to approximate the nonlinear hydrodynamic model with a linear parameter-varying one. Additionally, modeling uncertainties are incorporated into the other subsystem models of the AUV to capture the discrepancies between the outputs of the postulated mathematical abstractions and the experimental data. The resulting uncertain LFT system adequately captures the AUV behavior within a desired envelope. Ocean current disturbances are treated as uncertainties within the LFT system and properly characterized to reduce conservatism. The robust performance level, obtained from IQC analysis, serves as a qualitative measure of a controller’s performance, and is utilized in guiding the controller design process. The proposed approach is employed to design

H_{\infty}

and

H_{2}

controllers for the AUV. A comprehensive IQC-based analysis is subsequently conducted to demonstrate the robustness of the designed controllers to modeling uncertainties and disturbances. To validate the analysis results, extensive nonlinear simulations and underwater experiments are performed. The outcomes showcase the efficacy and reliability of the proposed approach in achieving robust control for the AUV.

本文采用基于积分二次约束（IQC）的鲁棒性分析框架，对自主潜水器（AUV）的路径跟踪控制器进行了设计和分析。AUV 被建模为不确定性线性分数变换 (LFT)，并受到测量噪声和洋流等外生输入的影响。所提出的方法利用基于学习的方法，用线性参数变化模型来近似非线性流体动力学模型。此外，在 AUV 的其他子系统模型中加入了建模不确定性，以捕捉假设的数学抽象输出与实验数据之间的差异。由此产生的不确定 LFT 系统可在所需范围内充分捕捉 AUV 的行为。洋流干扰被视为 LFT 系统中的不确定因素，并被适当描述以减少保守性。通过 IQC 分析获得的鲁棒性能水平可作为控制器性能的定性衡量标准，并用于指导控制器的设计过程。所提出的方法被用于为 AUV 设计 H∞ 和 H2 控制器。随后进行了基于 IQC 的综合分析，以证明所设计的控制器对模型不确定性和干扰的鲁棒性。为了验证分析结果，进行了大量的非线性模拟和水下实验。结果表明了所提出的方法在实现 AUV 鲁棒控制方面的有效性和可靠性。

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引用次数: 0

Time-optimal multi-point trajectory generation for robotic manipulators with continuous jerk and constant average acceleration 为具有连续颠簸和恒定平均加速度的机器人机械手生成时间最优多点轨迹

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-05 DOI: 10.1016/j.conengprac.2024.106154

Weiguang Yu , Daokui Qu , Fang Xu , Lei Zhang , Fengshan Zou , Zhenjun Du

To meet the demands of high-speed and high-accuracy applications of robotic manipulators, this paper proposes a time-optimal multi-point trajectory planning method with continuous jerk and constant average acceleration. A piecewise sine jerk model is developed for jerk continuity throughout the entire motion profile. An equivalent transformation of this complex model into the simple trapezoidal velocity model is proposed, effectively reducing the computational complexity and ensuring the reliability of real-time planning. The introduction of a parameter, named the trajectory smoothness coefficient, allows for a convenient trade-off between the priorities of speed and smoothness. The adaptive computation algorithm for peak jerk results in a constant average acceleration along paths of any length, ensuring a consistent level of work efficiency regardless of the density of path control points. Through a comprehensive evaluation of the critical constraints for each potential profile type, the single joint’s time-optimal and multiple joints’ time-synchronized planning problems are solved with closed-form solutions. Furthermore, by designing a multi-joint multi-point velocity look-ahead strategy, time-optimal multi-point trajectory planning for robotic manipulators is realized. Simulation and experimental results on a manipulator demonstrate the effectiveness of the proposed approach in improving time efficiency.

为满足机器人机械手高速、高精度的应用需求，本文提出了一种具有连续颠簸和恒定平均加速度的时间最优多点轨迹规划方法。为了实现整个运动曲线的颠簸连续性，本文开发了一种片状正弦颠簸模型。将这一复杂模型等效转换为简单的梯形速度模型，有效降低了计算复杂度，确保了实时规划的可靠性。通过引入一个名为轨迹平滑系数的参数，可以方便地权衡速度和平滑的优先级。峰值颠簸的自适应计算算法使得任何长度的路径都能获得恒定的平均加速度，从而确保了无论路径控制点的密度如何，都能达到一致的工作效率水平。通过对每种潜在轮廓类型的关键约束条件进行综合评估，单关节时间最优规划问题和多关节时间同步规划问题均以闭合形式求解。此外，通过设计多关节多点速度前瞻策略，实现了机器人机械手的时间最优多点轨迹规划。在机械手上进行的仿真和实验结果证明了所提出的方法在提高时间效率方面的有效性。

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引用次数: 0

Lane-free signal-free intersection crossing via model predictive control 通过模型预测控制实现无车道无信号交叉口穿越

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-05 DOI: 10.1016/j.conengprac.2024.106115

Mehdi Naderi , Panagiotis Typaldos , Markos Papageorgiou

The operation of signal-free intersections, where Connected Automated Vehicles (CAVs) cross simultaneously for all Origin-Destination (OD) movements, has the potential to greatly increase throughput and reduce fuel consumption. Since the intersection crossing areas naturally include no lanes, an extended crossing area, appropriately delineated, can be considered as a lane-free infrastructure so as to enable further efficiency benefits. This paper presents two Model Predictive Control (MPC) schemes to manage CAVs in signal-free and lane-free intersections. In fact, the control inputs of all vehicles are optimized over a time-horizon by online solving of a joint Optimal Control Problem (OCP) that minimizes a cost function including proper terms to ensure smooth and collision-free vehicle motion, while also considering fuel consumption and desired-speed tracking, when possible. Additionally, appropriate constraints are designed to respect the intersection boundaries and ensure smooth vehicle movements towards their respective destinations. A fast Feasible Direction Algorithm (FDA) is employed for the numerical solution of the introduced OCP. Multiple simulations are carried out to assess the efficiency and practicality of the proposed methods. A comparison with signalized intersection operation is provided.

在无信号灯交叉路口，互联自动驾驶车辆（CAV）可同时穿越所有起点-终点（OD）运动，这有可能大大提高吞吐量并降低油耗。由于交叉路口的交叉区域自然不包括车道，因此可将适当划定的扩展交叉区域视为无车道基础设施，从而进一步提高效率。本文提出了两种模型预测控制（MPC）方案，用于在无信号灯和无车道交叉路口管理 CAV。事实上，所有车辆的控制输入都是通过在线求解联合最优控制问题（OCP）在时间范围内进行优化的，该问题可使成本函数最小化，其中包括适当的条款，以确保车辆运动平稳、无碰撞，同时在可能的情况下还考虑到油耗和理想速度跟踪。此外，还设计了适当的约束条件，以尊重交叉路口的边界，确保车辆平稳地驶向各自的目的地。采用快速可行方向算法（FDA）对引入的 OCP 进行数值求解。为了评估所建议方法的效率和实用性，我们进行了多次模拟。此外，还提供了与信号灯路口运行的比较。

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引用次数: 0

Active disturbance rejection path tracking control of vehicles with adaptive observer bandwidth based on Q-learning 基于 Q-learning 的自适应观测器带宽的车辆主动干扰抑制路径跟踪控制

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-04 DOI: 10.1016/j.conengprac.2024.106137

Longqing Li , Kang Song , Guojie Tang , Wenchao Xue , Hui Xie , Jingping Ma

In this paper, a novel algorithm for vehicle path tracking control is introduced, focusing on maintaining tracking accuracy and minimizing steering wheel oscillation to enhance mechanism lifespan and passenger comfort. Vehicle kinematics model is utilized to formulate a second-order dynamic equation for lateral error, integrating yaw error into the standard first-order dynamic equation. A Proportional-Derivative (PD) controller is designed, incorporating an ‘extended state’ to compensate for the discrepancy between the model and actual vehicle dynamics, termed as the ‘total disturbance’. This ‘total disturbance’ is observed by an Extended State Observer (ESO), and a disturbance rejection law, combined with the PD controller, is employed to achieve the desired yaw rate. For improved vehicle safety and comfort, a dynamic constraint on the yaw rate, based on the vehicle’s motion and dynamic principles, is proposed. The vehicle’s nonlinear dynamics are addressed through feedback linearization, converting the target yaw rate into the required steering angle, which is then executed by the steer-by-wire system. An adaptive online algorithm for adjusting the ESO bandwidth, using Q-learning, is implemented. This optimization aims to balance tracking accuracy and steering wheel oscillation. A mathematical analysis confirms the stability of the time-varying bandwidth ESO and the overall system, ensuring limited estimation and control errors. Experimental comparison with the classical Stanley and Model Predictive Control (MPC) method demonstrates the algorithm’s effectiveness, maintaining lateral error within ±0.1 m.

本文介绍了一种新的车辆路径跟踪控制算法，重点是保持跟踪精度和尽量减少方向盘摆动，以提高机构寿命和乘客舒适度。利用车辆运动学模型制定了横向误差的二阶动态方程，并将偏航误差整合到标准的一阶动态方程中。设计了一个比例-派生（PD）控制器，其中包含一个 "扩展状态"，用于补偿模型与实际车辆动态之间的差异，即 "总干扰"。这种 "总扰动 "由扩展状态观测器（ESO）进行观测，并采用扰动抑制法则与 PD 控制器相结合，以实现所需的偏航率。为了提高车辆的安全性和舒适性，根据车辆的运动和动态原理，提出了偏航率动态约束。通过反馈线性化处理车辆的非线性动态，将目标偏航率转换为所需的转向角，然后由线控转向系统执行。利用 Q-learning 实现了调整 ESO 带宽的自适应在线算法。这种优化旨在平衡跟踪精度和方向盘振荡。数学分析证实了时变带宽 ESO 和整个系统的稳定性，确保了有限的估计和控制误差。与经典斯坦利和模型预测控制（MPC）方法的实验对比证明了该算法的有效性，可将横向误差保持在 ±0.1 米以内。

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引用次数: 0

Study of control strategy for cylinder-to-cylinder combustion homogeneity of marine medium-speed diesel engines 船用中速柴油机汽缸间燃烧均匀性控制策略研究

IF 5.4 2区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

Control Engineering Practice

Pub Date : 2024-11-04 DOI: 10.1016/j.conengprac.2024.106156

Shunhua Ou , Yonghua Yu , Nao Hu , Lei Hu , Jianguo Yang

Closed-loop combustion control (CLCC) is an efficient method for minimizing cylinder-to-cylinder combustion variation by adjusting individual cylinder fuel injection parameters. It is complementary to the closed-loop speed control, which precisely controls the engine speed by manipulating the global fuel injection parameters. However, the application of CLCC changed the conventional closed-loop speed control to a complex control structure. In addition, the selection of combustion control parameters will not only influence the combustion heat release control precisely, but also lead to increased calibration effort for the combustion controller. In this research, a triple closed-loop control strategy, in conjunction with a set-point online generation method, was proposed to improve the cylinder-to-cylinder combustion homogeneity, maintain the desired engine speed, and reduce the calibration effort simultaneously. A coefficient of variation in crank angle domain was utilized to analyze the cylinder-to-cylinder combustion homogeneity. The triple closed-loop control strategy was implemented on a marine medium-speed diesel engine. The experimental results indicated that the proposed control strategy, compared with the speed & IMEP (indicated mean effective pressure) cooperative control and speed & MFB50 (crank angle when 50 % fuel is consumed) cooperative control, has a better potential to alleviate cylinder-to-cylinder pressure variations at the same crankshaft angle. The cylinder-to-cylinder variation of IMEP and MFB50 decreased by 61 % and 38 % compared to the closed-loop speed control, respectively. The cylinder-to-cylinder combustion inhomogeneity, resulting from engine long-time operation and ambient conditions change, was significantly reduced as well. Therefore, the proposed strategy provides a multi-objective precise control method that allows the extension to low-carbon and zero-carbon marine engines.

闭环燃烧控制（CLCC）是一种通过调整单个气缸的燃油喷射参数来最大限度减少气缸间燃烧变化的有效方法。它是闭环转速控制的补充，后者通过操纵全局喷油参数来精确控制发动机转速。然而，CLCC 的应用改变了传统的闭环转速控制，使其成为一种复杂的控制结构。此外，燃烧控制参数的选择不仅会影响燃烧放热的精确控制，还会导致燃烧控制器的标定工作量增加。本研究提出了一种三重闭环控制策略，并结合设定点在线生成方法，以改善缸与缸之间的燃烧均匀性，保持理想的发动机转速，并同时减少标定工作量。利用曲柄角域的变化系数分析了气缸到气缸的燃烧均匀性。在船用中速柴油机上实施了三重闭环控制策略。实验结果表明，与转速& IMEP（指示平均有效压力）协同控制和转速& MFB50（消耗 50% 燃料时的曲柄角）协同控制相比，所提出的控制策略在相同曲轴角度下具有更好的缓解气缸到气缸压力变化的潜力。与闭环转速控制相比，IMEP 和 MFB50 的气缸间变化分别减少了 61% 和 38%。发动机长时间运行和环境条件变化导致的气缸间燃烧不均匀性也显著降低。因此，所提出的策略提供了一种多目标精确控制方法，可扩展到低碳和零碳船用发动机。

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引用次数: 0