Computationally efficient predictive cruise control of electric vehicles with nonsmooth system

IF 5.4 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Shiying Dong , Xi Luo , Yuxiang Zhang , Qifang Liu , Bingzhao Gao , Hong Chen
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引用次数: 0

Abstract

This paper presents a high-performance, computationally efficient predictive cruise control (HP-PCC) strategy aimed at enhancing the energy efficiency of autonomous electric vehicles. The original optimal control problem (OCP) formulation of the PCC problem introduces some nonsmooth terms, posing challenges for fast and accurate numerical solutions. To tackle this, we transform the widely studied PCC strategy into a numerically friendly smooth nonlinear programming (NLP) problem, without introducing extra simplification. We provide a rigorous proof of equivalence between the smoothed and original problems. To further boost computational efficiency, the resulting smooth NLP problem is solved by using a novel numerical procedure, which can improve the warm-start guess through inexpensive inexact Newton steps with a predicted initial value. Simulation results demonstrate that the proposed HP-PCC approach significantly outperforms existing methods in energy efficiency. Hardware-in-the-loop (HiL) experimental results show a reduction in energy consumption by 1% and a maximum computation time of less than 50 ms, confirming the feasibility of real-time implementation.
非光滑系统下电动汽车的高效预测巡航控制
本文提出了一种高性能、计算效率高的预测巡航控制(HP-PCC)策略,旨在提高自动驾驶电动汽车的能源效率。PCC问题的原始最优控制问题(OCP)公式引入了一些非光滑项,对快速准确的数值解提出了挑战。为了解决这个问题,我们将广泛研究的PCC策略转换为数值友好的光滑非线性规划(NLP)问题,而不引入额外的简化。我们给出了光滑问题与原始问题等价的严格证明。为了进一步提高计算效率,采用一种新的数值方法求解光滑NLP问题,该方法可以通过具有预测初值的廉价非精确牛顿步来改进热启动猜测。仿真结果表明,所提出的HP-PCC方法在能效方面明显优于现有方法。硬件在环(HiL)实验结果表明,能耗降低1%,最大计算时间小于50 ms,证实了实时实现的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Control Engineering Practice
Control Engineering Practice 工程技术-工程:电子与电气
CiteScore
9.20
自引率
12.20%
发文量
183
审稿时长
44 days
期刊介绍: Control Engineering Practice strives to meet the needs of industrial practitioners and industrially related academics and researchers. It publishes papers which illustrate the direct application of control theory and its supporting tools in all possible areas of automation. As a result, the journal only contains papers which can be considered to have made significant contributions to the application of advanced control techniques. It is normally expected that practical results should be included, but where simulation only studies are available, it is necessary to demonstrate that the simulation model is representative of a genuine application. Strictly theoretical papers will find a more appropriate home in Control Engineering Practice''s sister publication, Automatica. It is also expected that papers are innovative with respect to the state of the art and are sufficiently detailed for a reader to be able to duplicate the main results of the paper (supplementary material, including datasets, tables, code and any relevant interactive material can be made available and downloaded from the website). The benefits of the presented methods must be made very clear and the new techniques must be compared and contrasted with results obtained using existing methods. Moreover, a thorough analysis of failures that may happen in the design process and implementation can also be part of the paper. The scope of Control Engineering Practice matches the activities of IFAC. Papers demonstrating the contribution of automation and control in improving the performance, quality, productivity, sustainability, resource and energy efficiency, and the manageability of systems and processes for the benefit of mankind and are relevant to industrial practitioners are most welcome.
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