Experimental and analytical study of secondary path variations in active engine mounts

Hausberg, Fabian; Scheiblegger, Christian; Pfeffer, Peter E.; Plöchl, Manfred; Hecker, Simon; Rupp, Markus

doi:10.1016/j.jsv.2014.11.024

Cited by 41 publications

(37 citation statements)

References 48 publications

(92 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Filtered-X LMS algorithm has experienced a renaissance during the past years as it appears to be the right choice for vibration control in car engines [17][18][19][20]. A novel aspect here is that car engines can be controlled without sensors as the engine speed is known.…”

Section: Algorithm 4 Filtered-error Lms Algorithmmentioning

confidence: 99%

Adaptive filters: stable but divergent

Rupp

2015

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

The pros and cons of a quadratic error measure in the context of various applications have often been discussed. In this tutorial, we argue that it is not only a suboptimal but definitely the wrong choice when describing the stability behavior of adaptive filters. We take a walk through the past and recent history of adaptive filters and present 14 canonical forms of adaptive algorithms and even more variants thereof contrasting their mean-square with their l 2 −stability conditions. In particular, in safety critical applications, the convergence in the mean-square sense turns out to provide wrong results, often not leading to stability at all. Only the robustness concept with its l 2 −stability conditions ensures the absence of divergence.

show abstract

Section: Algorithm 4 Filtered-error Lms Algorithmmentioning

confidence: 99%

Adaptive filters: stable but divergent

Rupp

2015

EURASIP J. Adv. Signal Process.

Self Cite

View full text Add to dashboard Cite

show abstract

“…en, the theoretical model of the transfer function between the control force of the electromagnetic actuator and the output force of the AEM on the engine side was proposed, which was employed by Fakhari and Ohadi [20] for robust control. Considering the frequency-dependent characteristic of the volumetric stiffness of the main liquid chamber and the complex stiffness of the main rubber spring, Hausberg et al [21] proposed the model of the transfer function between the control voltage and the output force of the AEM on the engine side. e transfer function of the secondary path contains fluid dynamics in the inertia track and actuator dynamics, structural parameters of the cross-sectional area of the fluid channel, decouple plate, and main fluid chamber bulking.…”

Section: Introductionmentioning

confidence: 99%

“…Section 4 presents the analysis of the parameter effects, which is followed by the conclusions in Section 5. Figure 1 is selected for this study [1,21], which is mainly composed of a main rubber spring, two fluid chambers, an inertia track, a diaphragm, and a moving coil (voice coil) actuator. When the engine operates at low frequencies (engine starting, less than 20 Hz), the electromagnetic AEM works with the moving coil (voice coil) actuator turned off, which can be considered a passive traditional hydraulic engine mount (HEM).…”

Section: Introductionmentioning

confidence: 99%

Model of the Secondary Path between the Input Voltage and the Output Force of an Active Engine Mount on the Engine Side

Zhang

Shi

2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

e active engine mount (AEM) provides an effective solution to improve the acoustic and vibration comfort of a car. e same AEM can be installed for different engines and different vehicle bodies and attenuates the engine vibration, which is one of the most pressing challenges. To study this problem, this paper develops a mathematical model of a secondary path between the input voltage and output force of the AEM on the engine side considering the frequency-dependent characteristic of the stiffness, which includes the structure parameters of the AEM as well as the dynamics of the actuator, the fluid in the inertia track, the foundation (vehicle body), and the attenuated vibrating object (AEM preload or engine). e proposed model is validated by three test cases without vibration excitation, which are performed with different AEM preloads and foundations. e AEM is considered as an active part and passive part, the mass of which is determined experimentally. Parameter effect on the dynamic characteristics of the secondary path of the AEM is studied based on three tests and a numerical simulation.

show abstract

“…1 Active control engine mounts (ACMs) optimally dampen and isolate the vibrations, noises, and movements generated by a car's engine in different operating modes. Due to the hydraulic engine mount's inherent reliability in performance and adaptability to new designs, many researchers consider the hydraulic engine mount (HEM) 2 3 and a current shape control has been discussed in a Maxwell force type actuator for better control. 4 A linear oscillatory actuator using DC motor was developed for active engine mount in Kobayashi et al 5 Various control algorithms have been employed for ACMs.…”

Section: Introductionmentioning

confidence: 99%

“…15 It is common practice to incorporate an acceleration transducer or a load cell at the chassis side to provide an error signal to an adaptive algorithm. In most recent studies, 3,4 the transmitted force to the chassis is often measured as an error signal in a test rig. Experiments with a force transducer are conducted to validate the adaptive controller.…”

mentioning

confidence: 99%

Extended filtered-x-least-mean-squares algorithm for an active control engine mount based on acceleration error signal

Guo

Wei

Gao

2017

Advances in Mechanical Engineering

View full text Add to dashboard Cite

Active control engine mounts notably contribute to ensuring superior effectiveness in vibration suppression. The filtered-x-least-mean-squares algorithm, as a benchmark, is widely implemented for cancelation of disturbing engine vibrations. Such an algorithm requires an accurate secondary path estimate to ensure better performance. This study illustrates that incorporating body input point inertance to the active control engine mount model is necessary when accelerometers are utilized in most practical applications. Secondary path estimation errors caused by neglecting body input point inertance are pointed out via the secondary path modeling mismatch theory. Furthermore, the active control engine mount control system is evolved to fit the acceleration transducer applications. On the basis of the improved active control engine mount control system, a novel extended filtered-x-least-mean-squares algorithm based on the acceleration error signal is proposed to adapt to the extended control system. In the end, severe control collapse of secondary path estimation errors caused by neglecting body input point inertance is verified through simulation. Simulated results are presented to validate the performance of the extended filtered-x-least-mean-squares algorithm based on the acceleration error signal. The study demonstrates that the algorithm produces results showing effective vibration isolation. KeywordsActive control engine mount, body input point inertance, secondary path modeling mismatch, extended filtered-x-leastmean-squares algorithm, acceleration error signal Date

show abstract

Experimental and analytical study of secondary path variations in active engine mounts

Cited by 41 publications

References 48 publications

Adaptive filters: stable but divergent

Adaptive filters: stable but divergent

Model of the Secondary Path between the Input Voltage and the Output Force of an Active Engine Mount on the Engine Side

Extended filtered-x-least-mean-squares algorithm for an active control engine mount based on acceleration error signal

Contact Info

Product

Resources

About