Book ChapterDOI
A Model Predictive Approach for a Fuel Efficient Cruise Control System
Marcus Kalabis,Steffen Müller +1 more
- pp 201-211
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TLDR
Letting a dynamic distance towards an object vehicle decreases the subject vehicle’s fuel consumption because the engine can be run in fuel efficient operating points for a longer length of time.Abstract:
Many present-day’s vehicles are equipped with adaptive cruise control systems (ACC). The purpose of these systems is to keep a desired vehicle speed or distance towards a preceding object vehicle, if existing. Yet, present ACC systems do not consider the vehicle’s fuel consumption in a satisfactory way. For example, while platooning, a lot of fuel is wasted by vehicle drivers who imitate their respective preceding vehicles’ speed profiles. In contrast, copying these speed variations is not necessary, as it does not decrease the overall travel time but increases the fuel rate. Instead, allowing a dynamic distance towards an object vehicle decreases the subject vehicle’s fuel consumption because the engine can be run in fuel efficient operating points for a longer length of time.read more
Citations
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Journal ArticleDOI
Design and simulation of a real-time implementable energy-efficient model-predictive cruise controller for electric vehicles
TL;DR: The vehicle motion equation is reformulated in terms of the kinetic energy of the moving vehicle which leads to a linear differential equation without loss of information which lead to a model-predictive control approach with quadratic cost function, linear prediction model and linear constraints that corresponds to a piecewise linear system behaviour.
Journal ArticleDOI
A Minimum Principle-Based Algorithm for Energy-Efficient Eco-Driving of Electric Vehicles in Various Traffic and Road Conditions
TL;DR: An optimization algorithm for energy-efficient driving of electric vehicles based on Pontryagin's Minimum Principle, which handles the perturbation to the system dynamics and the constraints to the control and state variables.
Journal ArticleDOI
Energy-Optimal Adaptive Cruise Control for Electric Vehicles Based on Linear and Nonlinear Model Predictive Control
TL;DR: In this article, a nonlinear MPC (NMPC) formulation in space domain is proposed to overcome the drawbacks of LMPC in time domain, where the nonlinear equality constraints are relaxed to inequality constraints to yield a convex optimization problem and the relaxed optimization problem can be recast as a second-order cone programming (SOCP) problem, for which the efficient numerical optimizers exist.
Proceedings ArticleDOI
A Novel Model-Predictive Cruise Controller for Electric Vehicles and Energy-Efficient Driving
TL;DR: A model-predictive control approach with quadratic cost function, linear prediction model and linear constraints that corresponds to a piecewise linear system behaviour and allows a fast real-time implementation with guaranteed convergence is presented.
Proceedings ArticleDOI
Energy-Optimal Adaptive Cruise Control for Electric Vehicles Based on Nonlinear Model Predictive Control
TL;DR: A novel function of energy-optimal adaptive cruise control for electric vehicles based on model predictive control (MPC), which optimally plans the host car's speed trajectory for higher energy efficiency through taking the surrounding traffic information and the road conditions ahead into account is presented.
References
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Journal ArticleDOI
Integrating Traffic Data and Model Predictive Control to Improve Fuel Economy
TL;DR: Simulation results show the feasibility of the proposed approach to increasing fuel economy using traffic data and a model predictive controller on a passenger vehicle with minor hardware modifications required.