Automotive Sensors &amp; amp; Sensor Interfaces

Hammerschmidt, Dirk; Leteinturier, Patrick

doi:10.4271/2004-01-0210

Cited by 10 publications

(7 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hammerschimdt et al [37] assessed the role of sensors for an ECU in automotive applications. They state that there are two types of sensors: offshore and local.…”

Section: Applicationsmentioning

confidence: 99%

See 1 more Smart Citation

Review of Selection Criteria for Sensor and Actuator Configurations Suitable for Internal Combustion Engines

Comissiong¹,

Steffen²

2018

SAE Technical Paper Series

View full text Add to dashboard Cite

This literature review considers the problem of finding a suitable configuration of sensors and actuators for the control of an internal combustion engine. It takes a look at the methods, algorithms, processes, metrics, applications, research groups and patents relevant for this topic. Several formal metric have been proposed, but practical use remains limited. Maximal information criteria are theoretically optimal for selecting sensors, but hard to apply to a system as complex and nonlinear as an engine. Thus, we reviewed methods applied to neighboring fields including nonlinear systems and nonminimal phase systems. Furthermore, the closed loop nature of control means that information is not the only consideration, and speed, stability and robustness have to be considered. The optimal use of sensor information also requires the use of models, observers, state estimators or virtual sensors, and practical acceptance of these remains limited. Simple control metrics such as conditioning number are popular, mostly because they need fewer assumptions than closed-loop metrics, which require a full plant, disturbance and goal model. Overall, no clear consensus can be found on the choice of metrics to define optimal control configurations, with physical measures, linear algebra metrics and modern control metrics all being used. Genetic algorithms and multi-criterial optimisation were identified as the most widely used methods for optimal sensor selection, although addressing the dimensionality and complexity of formulating the problem remains a challenge. This review does present a number of different successful approaches for specific applications domains, some of which may be applicable to diesel engines and other automotive applications. For a thorough treatment, non-linear dynamics and uncertainties need to be considered together, which requires sophisticated (non-Gaussian) stochastic models to establish the value of a control architecture.

show abstract

“…Hammerschimdt et al [37] assessed the role of sensors for an ECU in automotive applications. They state that there are two types of sensors: offshore and local.…”

Section: Applicationsmentioning

confidence: 99%

“…This paper identifies that we must also review soft metrics for a complete optimization of the system. Hammerschmidt et al [37]…”

Section: Systems Engineeringmentioning

confidence: 99%

Review of Selection Criteria for Sensor and Actuator Configurations Suitable for Internal Combustion Engines

Comissiong¹,

Steffen²

2018

SAE Technical Paper Series

View full text Add to dashboard Cite

show abstract

“…A first example is the inversion of sensor dynamics (see Hammerschmidt and Leteinturier (2004) and Heywood (1988) for more details). A classic model of such a sensor is a first order dynamics with periodic excitation which can be, depending on the application, the intake pressure, the intake temperature, the exhaust pressure, the air fuel ratio, or the mass air flow ... For tutorial purpose, the system under consideration is…”

Section: Sensor Dynamic Inversionmentioning

confidence: 99%

“…In Section 2, we recall the problem statement and the procedure for the observer design. Then, in Section 3, a first example is the inversion of automotive sensor dynamics (see Hammerschmidt and Leteinturier (2004) and Heywood (1988) for more details). This will serve as a tutorial example to illustrate the convergence and the robustness of the observer design.…”

Section: Introductionmentioning

confidence: 99%

Asymptotic reconstruction of the Fourier expansion of inputs of linear time-varying systems with applications

Chauvin

Petit

2010

IFAC Proceedings Volumes

View full text Add to dashboard Cite

Linear time-varying systems driven by periodic input signals are ubiquitous in control systems. For various reasons, including disturbance rejection and diagnosis by analysis of the trajectories, estimation of their input signals is often desirable. In the present paper, we illustrate a recently proposed general method to solve such problems by an asymptotic reconstruction of the Fourier expansion of the unknown input signal along with several examples from the automotive engine industry, and with an oscillating water column retrieving wave energy.

show abstract

“…At various level of modelling, automotive engine dynamics can be considered as a linear periodic system mechanically coordinated through the revolution of the crankshaft. A prime example is the inversion of sensor dynamics (Zone 1 on Figure 1) (see [1] and [2] for more details). A classical model of such a sensor is a first order dynamics with periodic excitation which can be, depending on the application, the intake pressure, the intake temperature, the exhaust pressure, the Air Fuel Ratio, or the Mass Air Flow.…”

Section: Introductionmentioning

confidence: 99%

Periodic Input Observer Design: Application for Imbalance Diagnosis

Chauvin

Petit

Rouchon

et al. 2006

SAE Technical Paper Series

View full text Add to dashboard Cite

Observation problems have been garnering increasing attention in recent years. They can be seen as the estimation of a periodic output dynamics driven by periodic inputs. At various level of modelling, automotive engine dynamics can be considered as a linear periodic system mechanically coordinated through the revolution of the crankshaft. In this paper, two practical examples are addressed. The first example is the inversion of sensor dynamics. A classical way of modelling such a sensor is a first order dynamics with periodic excitations which can be, depending on the application, the intake pressure, the intake temperature, the exhaust pressure, the Air Fuel Ratio, or the Mass Air Flow. The second example is the estimation of the engine speed next to the cylinder using as only sensor the easily available instantaneous crankshaft angle speed at the end of the connecting rod.The contribution of this paper is the design of a real-time observer of the periodic excitation of a linear periodic systems by the estimation of the Fourier decomposition of the signal. The estimation of the coefficients of the Fourier basis decomposition of the input periodic excitation is a handy tool for engineering purposes. Indeed, the energy levels of the signal allow another interpretation of the signal and can lead to detect the balance of the engine. This high frequency (6 o crankshaft estimation) information can be used for imbalance diagnosis and torque balance control. Real application observation problems are exposed in their practical context and illustrated by experimental results on a 4 cylinder HCCI engine.

show abstract

Automotive Sensors & amp; Sensor Interfaces

Cited by 10 publications

References 4 publications

Review of Selection Criteria for Sensor and Actuator Configurations Suitable for Internal Combustion Engines

Review of Selection Criteria for Sensor and Actuator Configurations Suitable for Internal Combustion Engines

Asymptotic reconstruction of the Fourier expansion of inputs of linear time-varying systems with applications

Periodic Input Observer Design: Application for Imbalance Diagnosis

Contact Info

Product

Resources

About