Design of computer experiments for open-loop control and robustness analysis of clutch-to-clutch shifts in automatic transmissions

Yoon, Albert; Khargonekar, Pramod P.; Hebbale, Kumaraswamy

doi:10.1109/acc.1997.612088

Cited by 18 publications

(7 citation statements)

References 8 publications

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“…The problem of designing risk-adjusted controllers has been considered in several papers, e.g., see [1], [2], [3], and [4]. However, there is a fundamental difference between the work mentioned above and the results presented in this paper.…”

Section: Introductionmentioning

confidence: 94%

Probabilistically Constrained Linear Programs and Risk-Adjusted Controller Design

Lagoa¹,

Li²,

Sznaier³

2005

SIAM J. Optim.

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The focal point of this paper is the probabilistically constrained linear program (PCLP) and how it can be applied to control system design under risk constraints. The PCLP is the counterpart of the classical linear program, where it is assumed that there is random uncertainty in the constraints and, therefore, the deterministic constraints are replaced by probabilistic ones. It is shown that for a wide class of probability density functions, called log-concave symmetric densities, the PCLP is a convex program. An equivalent formulation of the PCLP is also presented which provides insight into numerical implementation. This concept is applied to control system design. It is shown how the results in this paper can be applied to the design of controllers for discrete-time systems to obtain a closed loop system with a well-defined risk of violating the so-called property of superstability. Furthermore, we address the problem of risk-adjusted pole placement.

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Section: Introductionmentioning

confidence: 94%

Probabilistically Constrained Linear Programs and Risk-Adjusted Controller Design

Lagoa¹,

Li²,

Sznaier³

2005

SIAM J. Optim.

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“…Torque phase control has been mostly accomplished using open-loop techniques [66,39,117], given the relative paucity of sensor information during this phase. Consequently, articles dedicated to torque phase control are far fewer than for inertia phase control are where the technical literature is comparatively rich.…”

Section: Powertrain Control and Estimationmentioning

confidence: 99%

Robust nonlinear estimation and control of clutch-to-clutch shifts

Mishra

Srinivasan

2016

2016 American Control Conference (ACC)

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Shift quality is an integral component of drivability. Thus, with the extension of feedback control to more powertrain functions, it is of paramount importance that systematic and robust control methods be developed for ensuring good shift quality. Increasingly, automatic transmissions employ a combination of two actively controlled clutches to implement shifts, which makes the gearshifts clutch-to-clutch shifts. In the current study, a model-based approach is presented for the development of a robust clutch-to-clutch shift controller. A detailed nonlinear model of the powertrain consisting of engine, torque converter, transmission system, and vehicle dynamics is developed. The transmission system consists of mechanical and hydraulic subsystems. While the mechanical subsystem is easier to model, the hydraulic subsystem, commonly referred to as shift hydraulic system, is usually challenging to model due to high dynamic order and significant nonlinearities. Starting from a high order nonlinear model of the shift hydraulic dynamics, developed from first principles in an earlier study, we apply systematic methods to arrive at a lower order control-oriented model, and use it to develop a closed loop clutch pressure controller. Specifically, state-space averaging and singular perturbation techniques were used to achieve this. The reduced order model was validated against experimental measurements.

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“…Assuming that the gear wheels are rigid, the kinematics of the planetary gear can be described by using the conditions of pure rolling. [9] in out T R T ⋅ = (7) out in n R n ⋅ = (8) Where T in is the input torque of torque converter; T out is the output torque of torque converter; n in and n out are input and output speed of torque converter respectively; R is each gear ratio of transmission.…”

Section: Planetary Transmission Modelmentioning

confidence: 99%

“…All the relationships between engine rotational speed and friction resistance, between engine rotational speed and fan resistance, between engine rotational speed and pump wheel torque are approximately linear. The dynamic model of engine is as formula (3) [7,8] B e e ei T T n I − = .…”

Section: Engine Modelmentioning

confidence: 99%

Study on Intelligent Shift Control Strategy of Automobile Based on Genetic-Fuzzy Algorithm

Zhu

et al. 2008

2008 3rd International Conference on Innovative Computing Information and Control

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In order to improve automobile transfer efficiency, we design a fuzzy control strategy based on genetic algorithm. Acceleration is taken as a control parameter of automatic transmission upshifting or downshifting, namely that only when acceleration is positive, automobile can be upshifted, only when acceleration is negative or zero, automobile can be downshifted. Two different fuzzy controllers are respectively used to control upshifting and downshifting. Fuzzy controllers are designed according shift maps obtained from experimental. Genetic algorithm is used to optimize the fuzzy controllers and the simulation model is built to achieve the control strategy. The results of simulation show: automobile with this shift strategy can effectively avoid shift cycle even if it is running in complicated driving conditions, this shift strategy improves automobile power and economy performance and the optimization by genetic algorithm improves the design efficiency of controllers and the shift quality.

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Design of computer experiments for open-loop control and robustness analysis of clutch-to-clutch shifts in automatic transmissions

Cited by 18 publications

References 8 publications

Probabilistically Constrained Linear Programs and Risk-Adjusted Controller Design

Probabilistically Constrained Linear Programs and Risk-Adjusted Controller Design

Robust nonlinear estimation and control of clutch-to-clutch shifts

Study on Intelligent Shift Control Strategy of Automobile Based on Genetic-Fuzzy Algorithm

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