Real-Time Velocity Optimization for Energy-Efficient Control of Connected and Automated Vehicles

Abstract This paper presents a fast numerical algorithm for velocity optimization based on the Pontryagin' minimum principle (PMP). Considering the difficulties in the application of the PMP when state constraints exist, the penalty function approach is proposed to convert the state-constrained problem into an unconstrained one. Then this paper proposes an iterative numerical algorithm by using the explicit solution to find the optimal solution. The proposed numerical algorithm is applied to the velocity trajectory optimization for energy-efficient control of connected and automated vehicles (CAVs). Simulation results indicate that the algorithm can generate the optimal inputs in milliseconds, and a significant improvement in computational efficiency compared with traditional methods (a few seconds). Hardware in the Loop test for experimental validation is given to further verify the real-time performance of the proposed algorithm.

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Implementing a Real-Time, Energy-Efficient Control Methodology to Maximize Manufacturing Profits

IEEE Transactions on Systems Man and Cybernetics Systems ◽

10.1109/tsmc.2015.2450679 ◽

2016 ◽

Vol 46 (6) ◽

pp. 855-866 ◽

Cited By ~ 13

Author(s):

Michael P. Brundage ◽

Qing Chang ◽

Yang Li ◽

Jorge Arinez ◽

Guoxian Xiao

Keyword(s):

Real Time ◽

Energy Efficient ◽

Efficient Control ◽

Control Methodology

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Control and Powertrain Management for Multi-Autonomous Hybrid Vehicles

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4043110 ◽

2019 ◽

Vol 141 (7) ◽

Author(s):

Masood Ghasemi ◽

Xingyong Song

Keyword(s):

Real Time ◽

Fuel Consumption ◽

Autonomous Vehicles ◽

Minimum Principle ◽

Optimal Solution ◽

Algebraic Equations ◽

Computationally Efficient ◽

Hybrid Powertrain ◽

Fuel Consumption Rate ◽

Optimal Approach

The need for less fuel consumption and the trend of higher level of autonomy together urge the power optimization in multihybrid autonomous vehicles. Both the multivehicle coordination control and the hybrid powertrain energy management should be optimized to maximize fuel savings. In this paper, we intend to have a computationally efficient framework to optimize them individually and then evaluate the overall control performance. The optimization is conducted in series. First is at the multivehicle system's level where the distributed locally optimal solution is given for vehicles with nonlinear dynamics. Second, the powertrain management optimization is conducted at the hybrid powertrain level. We provide an analytical formulation of the powertrain optimization for each hybrid vehicle by using Pontryagin's minimum principle (PMP). By approximating the optimal instantaneous fuel consumption rate as a polynomial of the engine speed, we can formulate the optimization problem into a set of algebraic equations, which enables the computationally efficient real-time implementation. To justify the applicability of the methodology in real-time, we give directions on numerical iterative solutions for these algebraic equations. The analysis on the stability of the method is shown through statistical analysis. Finally, further simulations are given to confirm the efficacy and the robustness of the proposed optimal approach. An off-road example is given in the simulation, although the framework developed can be applied to on-road scenario as well.

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Energy-Efficient Connected and Automated Vehicles: Real-Time Traffic Prediction-Enabled Co-Optimization of Vehicle Motion and Powertrain Operation

IEEE Vehicular Technology Magazine ◽

10.1109/mvt.2021.3085999 ◽

2021 ◽

pp. 2-11

Author(s):

Yunli Shao ◽

Zongxuan Sun

Keyword(s):

Real Time ◽

Energy Efficient ◽

Traffic Prediction ◽

Automated Vehicles ◽

Real Time Traffic ◽

Vehicle Motion

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Real-Time Energy-Efficient Control for Fully Electric Vehicles Based on an Explicit Model Predictive Control Method

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2018.2806400 ◽

2018 ◽

Vol 67 (6) ◽

pp. 4693-4701 ◽

Cited By ~ 18

Author(s):

Shuwei Zhang ◽

Yugong Luo ◽

Keqiang Li ◽

Victor Li

Keyword(s):

Model Predictive Control ◽

Real Time ◽

Predictive Control ◽

Electric Vehicles ◽

Energy Efficient ◽

Control Method ◽

Explicit Model ◽

Explicit Model Predictive Control ◽

Efficient Control

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Determining Model Accuracy Requirements for Automotive Engine Coldstart Hydrocarbon Emissions Control

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.4006217 ◽

2012 ◽

Vol 134 (5) ◽

Cited By ~ 17

Author(s):

Nasser L. Azad ◽

Pannag R. Sanketi ◽

J. Karl Hedrick

Keyword(s):

Optimal Control ◽

Sensitivity Analysis ◽

Real Time ◽

Minimum Principle ◽

Optimal Solution ◽

Control Performance ◽

Automotive Engine ◽

Engine Model ◽

Time Optimal ◽

Hc Emissions

In this work, a systematic method is introduced to determine the required accuracy of an automotive engine model used for real-time optimal control of coldstart hydrocarbon (HC) emissions. The engine model structure and development are briefly explained and the model predictions versus experimental results are presented. The control design problem is represented with a dynamic optimization formulation on the basis of the engine model and solved using the Pontryagin’s minimum principle (PMP). To relate the level of plant/model mismatch and the control performance degradation in practice, a sensitivity analysis using a computationally efficient method is employed. In this way, the sensitivities or the effects of small parameter variations on the optimal solution, which is the minimum of cumulative tailpipe HC emissions over the coldstart period, are calculated. There is a good agreement between the sensitivity analysis results and the experimental data. The sensitivities indicate the directions of the subsequent parameter estimation and model improvement tasks to enhance the control-relevant accuracy, and thus, the control performance. Furthermore, they provide some insights to simplify the engine model, which is critical for real-time implementation of the coldstart optimal control system.

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Real-time and contactless measurements of thermal discomfort based on human poses for energy efficient control of buildings

Building and Environment ◽

10.1016/j.buildenv.2019.106284 ◽

2019 ◽

Vol 162 ◽

pp. 106284 ◽

Cited By ~ 6

Author(s):

Bin Yang ◽

Xiaogang Cheng ◽

Dengxin Dai ◽

Thomas Olofsson ◽

Haibo Li ◽

...

Keyword(s):

Real Time ◽

Energy Efficient ◽

Thermal Discomfort ◽

Efficient Control ◽

Contactless Measurements

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A Trajectory Optimization Strategy for Connected and Automated Vehicles at Junction of Freeway and Urban Road

Sustainability ◽

10.3390/su13179933 ◽

2021 ◽

Vol 13 (17) ◽

pp. 9933

Author(s):

Zhongtai Jiang ◽

Dexin Yu ◽

Huxing Zhou ◽

Siliang Luan ◽

Xue Xing

Keyword(s):

Trajectory Optimization ◽

Minimum Principle ◽

Optimization Strategy ◽

Automated Vehicles ◽

Simulation Experiments ◽

Urban Road ◽

Second Stage ◽

Stop And Go ◽

Vehicle Trajectory ◽

Junction Structure

The phenomenon of stop-and-go traffic and its environmental impact has become a crucial issue that needs to be tackled, in terms of the junctions between freeway and urban road networks, which consist of freeway off-ramps, downstream intersections, and the junction section. The development of Connected and Automated Vehicles (CAVs) has provided promising solutions to tackle the difficulties that arise along intersections and freeway off-ramps separately. However, several problems still exist that need to be handled in terms of junction structure, including vehicle merging trajectory optimization, vehicle crossing trajectory optimization, and heterogeneous decision-making. In this paper, a two-stage CAV trajectory optimization strategy is presented to improve fuel economy and to reduce delays through a joint framework. The first stage considers an approach to determine travel time considering the different topological structures of each subarea to ensure maximum capacity. In the second stage, Pontryagin’s Minimum Principle (PMP) is employed to construct Hamiltonian equations to smooth vehicle trajectory under the requirements of vehicle dynamics and safety. Targeted methods are devised to avoid driving backwards and to ensure an optimal vehicle gap, which make up for the shortcomings of the PMP theory. Finally, simulation experiments are designed to verify the effectiveness of the proposed strategy. The evaluation results show that our strategy could effectively militate travel delays and fuel consumption.

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Designing a Knowledge base for Intelligent Information System of MIMO Control

Information and Control Systems ◽

10.31799/1684-8853-2018-4-24-30 ◽

2018 ◽

pp. 24-30

Author(s):

D. Yu. Muromtsev ◽

A. N. Gribkov ◽

I. V. Tyurin ◽

V. N. Shamkin

Keyword(s):

Control System ◽

Knowledge Base ◽

Real Time ◽

Energy Efficient ◽

Mimo Systems ◽

Control Object ◽

Information Control ◽

Control Actions ◽

Efficient Control ◽

Intelligent Information

Introduction: The problem of designing information control systems for MIMO systems requires a comprehensive analysis of their operational and technological regimes. Artificial intelligence methods can be used to solve problems related to building models and their optimization in conditions of uncertainty when it is necessary to make prompt decisions.Purpose:Developing a methodology for designing an intelligent information control system which would be invariant to various MIMO systems and could promptly synthesize energy-efficient control actions in real time, taking into account the features of these objects.Results:A static model has been developed for a frame-based knowledge base of an information-control system for energy-intensive process plants in dynamic operation modes. It allows you to take into account the number of states of the operating capability of the control object, many states of its operation, and destabilizing factors of various types. An integrated graph is proposed for generalized intellectualization technology of synthesizing energy-saving control actions for MIMO thermal facilities in warm-up mode.Practical relevance: The created knowledge base structure allows you to promptly provide information for modules realizing algorithmic support of an intelligent information and control system, which in turn makes it possible to synthesize energy-efficient control of a MIMO thermal facility in real time. In addition, energysaving control is characterized by a smooth flow of thermal processes, and this leads to increased durability and safety of the equipment operation.

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