Automotive Powertrain Control — A Survey

This paper surveys recent and historical publications on automotive powertrain control. Control‐oriented models of gasoline and diesel engines and their aftertreatment systems are reviewed, and challenging control problems for conventional engines, hybrid vehicles and fuel cell powertrains are discussed. Fundamentals are revisited and advancements are highlighted. A comprehensive list of references is provided.     

Model predictive control of magnetically actuated mass spring dampers for automotive applications

Mechatronic systems such as those arising in automotive applications are characterized by significant non-linearities, tight performance specifications as well as by state and input constraints which need to be enforced during system operation. This paper takes a view that model predictive control (MPC) and hybrid models can be an attractive and systematic methodology to handle these challenging control problems, even when the underlying process is not hybrid. In addition, the piecewise affine (PWA) explicit form of MPC solutions avoids on-line optimization and can make this approach computationally viable even in situations with rather constrained computational resources. To illustrate the MPC design procedure and the underlying issues, we focus on a specific non-linear process example of a mass spring damper system actuated by an electromagnet. Such a system is one of the most common elements of mechatronic systems in automotive systems, with fuel injectors representing a concrete example. We first consider a linear MPC design for the mechanical part of the system. The approach accounts for all the constraints in the system but one, which is subsequently enforced via a state-dependent saturation element. Second, a hybrid MPC approach for the mechanical subsystem is analysed that can handle all the constraints by design and achieves better performance, at the price of a higher complexity of the controller. Finally, a hybrid MPC design that also takes into account the electrical dynamics of the system is considered.     

An Integrated Software Environment For Powertrain Feasibility Assessment Using Optimization And Optimal Control

With the increase in automotive powertrain complexity, an upfront assessment of powertrain capability in meeting its design targets is important early on in the development programs. The optimization of control policy based on powertrain simulation models can facilitate this assessment and establish limits of achievable performance for a given powertrain configuration and parameters. The paper discusses several computational optimization and user interface solutions for deploying a numerical optimal control approach in a user‐friendly software environment.     

On the dynamics and control of through-plane water distributions in PEM fuel cells

We provide a semi-analytic solution to simplify an experimentally validated numeric realization of a two-phase, reaction-diffusion, distributed parameter model of the through-plane water distributions as they evolve inside polymer electrolyte membrane (PEM) fuel cell gas diffusion layers. The semi-analytic solution is then analyzed for stability and to gain insight into the dynamics of the equilibrium (steady-state) water distributions. Candidate distributions for vapor and liquid water are then identified which allow maximum membrane hydration while simultaneously avoiding voltage degradation that results from anode liquid water accumulation (flooding). The desired anode water distributions could be maintained via control of the anode channel conditions (boundary value control) with the ultimate goal to maximize the hydrogen utilization and prolong fuel cell life.     

Reduced order extended command governor

Extended command governors (ECGs) are add-on schemes that modify set-point commands as necessary to ensure that imposed state and control constraints are not violated by closed-loop systems designed for set-point tracking. In this paper, we propose a reduced order ECG for systems with dynamics decomposable into slow and fast state variables. We demonstrate that ECG implementation can be based on slow states only, thus reducing the computational complexity. This is achieved by introducing additional constraints, and by slightly tightening the original constraints. We demonstrate that the proposed ECG maintains the response properties of the conventional ECG, including the convergence to the nearest feasible command in finite time in the case of constant reference commands. The results are also shown to apply to conventional command governors. For the case when the reduced order state is not directly measured, a formulation of the result in the presence of a state observer is developed.     

Optimal control of continuous-time linear systems with a time-varying, random delay

We study a finite horizon optimal control problem for a class of linear systems with a randomly varying time-delay. The systems of this type may arise in embedded control applications and in certain applications in economics. The delay value is treated as an unknown variable but with known statistical properties, modelled by a Markov process with a finite number of states. The “probabilistic delay averaging” approach is employed to determine the optimal control in the form which is independent of the delay value.     

Simultaneous input and parameter estimation with input observers and set‐membership parameter bounding: theory and an automotive application

The paper addresses an on‐line, simultaneous input and parameter estimation problem for a first‐order system affected by measurement noise. This problem is motivated by practical applications in the area of engine control. Our approach combines an input observer for the unknown input with a set‐membership algorithm to estimate the parameter. The set‐membership algorithm takes advantage of a priori available information such as (i) known bounds on the unknown input, measurement noise and time rate of change of the unknown input; (ii) the form of the input observer in which the unknown parameter affects only the observer output; and (iii) the input observer error bounds for the case when the parameter is known exactly. The asymptotic properties of the algorithm as the observer gain increases are delineated. It is shown that for accurate estimation the unknown input needs to approach the known bounds a sufficient number of times (these time instants need not be known). Powertrain control applications are discussed and a simulation example based on application to engine control is reported. A generalization of the basic ideas to higher order systems is also elaborated. Copyright © 2006 John Wiley & Sons, Ltd.     

New results on control of multibody systems which conserve angular momentum

A planar system of rigid bodies interconnected by one degree of freedom rotational joints is considered. This multibody system is referred to as a multilink, and the rigid bodies are referred to as links. The angular momentum of the multilink is conserved but is not necessarily zero. We show that if the number of links is at least four, then periodic joint motions can make the absolute orientation of a specified base link track exactly a specified function of time whose time derivative is periodic. This result on the use of periodic joint motions for orientation tracking extends previous work [15], [20], [22] on using periodic joint motions for rest-to-rest reorientation. It has interesting physical consequences. Specifically, in the case of non-zero angular momentum periodic joint motions can maintain the orientation of the base link constant. In the case of zero angular momentum periodic joint motions can change the orientation of the base link at a specified angular rate. We also demonstrate that if the multilink consists of at least three links, then for any value of the angular momentum joint motions can reorient the multilink arbitrarily over anarbitrary time interval. This result extends similar results in [15] for zero angular momentum and in [20] that apply for nonzero angular momentum but not for an arbitrary time interval. In terms of their control-theoretic aspects, the problems treated in the paper can be viewed as controllability problems for a class of nonlinear control system with time-dependent drift.     

Application of input estimation techniques to charge estimation and control in automotive engines

The performance of control, estimation and diagnostics algorithms of modern automotive engine management systems can be significantly enhanced using input observers. This paper describes several case studies along these lines in the area of charge estimation and control for gasoline and diesel engines, and illustrates the conclusions with experimental results obtained from a vehicle and from an engine dynamometer. A self-contained overview of some of the popular input estimation techniques and their properties is provided. Pointers are given that show how input estimators can be integrated within more complex adaptation and control algorithms using specific automotive applications as examples.     

Preserving stability/performance when facing an unknown time-delay

Embedded controllers executed in real-time are, frequently, subject to a time-varying delay induced by task prioritization or communication over prioritized communication networks. Depending on the microprocessor or network load the delay value may vary. The control design that is based on the worst case assumption with respect to the delay may be very conservative and fail to deliver the adequate performance. On the other hand, the price for not properly dealing with the delay is instability. In this paper some of these issues are discussed in more detail and a control scheme is proposed which combines an unknown input observer to estimate the delayed value of the input, an on-line estimation scheme for the delay and a controller that adjusts its gains as needed to preserve system stability. Some of the aspects of the proposed scheme are discussed and illustrated with simulations on an automotive example.