Integration of in-wheel motor sensorless systems and hierarchical direct yaw moment control for distributed drive electric vehicles

IF 7.5 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS Engineering Applications of Artificial Intelligence Pub Date : 2024-11-11 DOI:10.1016/j.engappai.2024.109600
Xiaodong Wang , Maoping Ran , Xinglin Zhou
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Abstract

Ensuring robust and reliable control of distributed vehicles powered by in-wheel motor systems poses a significant challenge due to the harsh operating environments and high costs of such motor systems. Poor motor control, parameter variations, and sensor malfunction under these conditions can compromise the vehicle yaw stability. Integrating permanent magnet synchronous motor (PMSM) sensorless systems with vehicle yaw moment control offers a cost-effective solution for this issue without wheel angular speed sensors while enhancing yaw stability. In this paper, a composite nonlinear feedback sliding mode controller that can enhance the PMSM speed response is proposed. The proposed scheme exhibits a rotor speed overshoot and transient time of only 0.64% and 0.07s, respectively, which are smaller and shorter compared with other methods under motor parameter changes. Subsequently, the key states and tire-road friction coefficients required for vehicle control were estimated using sensorless rotor speeds and unscented Kalman filters, enabling the integration of the PMSM sensorless system with the vehicle yaw moment control. Additionally, a fuzzy adaptive hybrid sliding mode method is presented for yaw moment control enhancement. This method maintained the smallest sideslip angle root mean square error during double lane changes (0.4192 deg) compared with other methods. Analysis results show that different motor controllers and parameter changes significantly affect the vehicle dynamics performance. The proposed integrated scheme is feasible and effectively enhances the yaw moment control via high-performance sensorless PMSM systems.
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集成轮内电机无传感器系统和分层直接偏航力矩控制,用于分布式驱动电动汽车
由于轮内电机系统的运行环境恶劣且成本高昂,因此确保对由轮内电机系统驱动的分布式车辆进行稳健可靠的控制是一项重大挑战。在这些条件下,电机控制不良、参数变化和传感器故障都会影响车辆的偏航稳定性。将永磁同步电机(PMSM)无传感器系统与车辆偏航力矩控制相结合,可在不使用车轮角速度传感器的情况下为这一问题提供经济有效的解决方案,同时增强偏航稳定性。本文提出了一种可增强 PMSM 速度响应的复合非线性反馈滑模控制器。在电机参数变化的情况下,所提方案的转子速度过冲和瞬态时间分别仅为 0.64% 和 0.07s,与其他方法相比更小、更短。随后,利用无传感器转子速度和无特征卡尔曼滤波器估算了车辆控制所需的关键状态和轮胎与路面摩擦系数,从而实现了 PMSM 无传感器系统与车辆偏航力矩控制的集成。此外,还介绍了一种用于增强偏航力矩控制的模糊自适应混合滑动模式方法。与其他方法相比,该方法在双线变道时保持了最小的侧滑角均方根误差(0.4192 度)。分析结果表明,不同的电机控制器和参数变化会显著影响车辆动力学性能。所提出的集成方案是可行的,能通过高性能无传感器 PMSM 系统有效增强偏航力矩控制。
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来源期刊
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence 工程技术-工程:电子与电气
CiteScore
9.60
自引率
10.00%
发文量
505
审稿时长
68 days
期刊介绍: Artificial Intelligence (AI) is pivotal in driving the fourth industrial revolution, witnessing remarkable advancements across various machine learning methodologies. AI techniques have become indispensable tools for practicing engineers, enabling them to tackle previously insurmountable challenges. Engineering Applications of Artificial Intelligence serves as a global platform for the swift dissemination of research elucidating the practical application of AI methods across all engineering disciplines. Submitted papers are expected to present novel aspects of AI utilized in real-world engineering applications, validated using publicly available datasets to ensure the replicability of research outcomes. Join us in exploring the transformative potential of AI in engineering.
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