Modelling and analysis of an active suspension 1/4 of vehicle with bond graph

Khemliche, M.; Dif, I.; Latrèche, S.; Bouamama, Belkacem Ould

doi:10.1109/isccsp.2004.1296569

Cited by 7 publications

(4 citation statements)

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“…The synthesis of a control law is generally based on a model describing the behavior of the system under study. Physical systems vary from linear [15] to non-linear [16] and may or may not vary in time with several control techniques to regulate or track trajectory, leading to several control laws which may be linear such as the LQR control [17], LQR control based on bond graph model [18], PID and Intelligent PID control [19], and nonlinear control in several techniques based on graphical model (bond graph) [20][21], mathematical model (CTC, VSC, backstepping, H ∞ , MPC, etc.) [22][23][24], or intelligent and meta-heuristic model optimization [19,[25][26], etc.…”

Section: Trajectory-tracking Control By Bond Graphmentioning

confidence: 99%

“…The error between the desired and the tracked velocity is around 10% from the nominal value, which is accepted in a control law. The contribution of this work is in the use of graphical and algebraic properties of the bond graph tool for the design of the control law, when the model is in presence of uncertainties, without the need for mathematical equation derivation, such as used in [18,[20][21]. For the implementation of this control law, a platform is needed that integrates bond graph models, such as the 20-sim software in later versions than the one used in this paper, which allow interaction with practical systems.…”

Section: Uncertainty In Bond Graphmentioning

confidence: 99%

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Trajectory Tracking Control Design of a Mass-Damping-Spring System with Uncertainty using the Bond Graph Approach

Dif¹,

Kouzou²,

Benmahammed³

et al. 2020

Eng. Technol. Appl. Sci. Res.

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This paper deals with the simulation, and design of a trajectory-tracking control law for a physical system under parameter uncertainty modeled by a bond graph. This control strategy is based on the inversion of the system through their causal Input/Output (I/O) path using the principle of bicausality to track the desired trajectory. The proposed control strategy is validated with the use of a simple mechanical mass-spring-damper system. The results show that the bond graph is a very helpful methodology for the design of control laws in the presence of uncertainties. This proposed control can be applied in several applications and can be improved to ensure robust control.

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Section: Trajectory-tracking Control By Bond Graphmentioning

confidence: 99%

Section: Uncertainty In Bond Graphmentioning

confidence: 99%

Trajectory Tracking Control Design of a Mass-Damping-Spring System with Uncertainty using the Bond Graph Approach

Dif¹,

Kouzou²,

Benmahammed³

et al. 2020

Eng. Technol. Appl. Sci. Res.

Self Cite

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“…La técnica Bond Graph relaciona los componentes del sistema mediante su intercambio de energía, lo que resultaútil para el modelado completo de un vehículo (Silva et al, 2008) (Margolis and Shim, 2001). Esta técnica se puede implementar en entornos de programación como Dymola (Silva et al, 2008) o Simulink (Khemliche et al, 2004). Mediante Bond Graph se pueden revelar las diferencias entre la potencia del actuador y sus requerimientos de energía en una suspensión activa (Karnopp and So, 1998), comparar diferentes tipos de suspensión en un modelo de un cuarto de vehículo (Khemliche et al, 2004), o diseñar la estructura de la suspensión con algoritmos evolutivos (Wang et al, 2005).…”

Section: El Modelado Y Simulación De La Dinámica Vehícularunclassified

Los Sistemas de Suspensión Activa y Semiactiva: Una Revisión

Hurel

Mandow

García-Cerezo

2013

Revista Iberoamericana de Automática e Informática Industrial R

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El propósito de este artículo es efectuar una revisión del estado del conocimiento en el modelado y control de los sistemas de suspensión activa y semiactiva. Se analizan las principales características de los diferentes tipos de sistemas de suspensión: pasiva, activa y semiactiva. Respecto al modelado y simulación de los sistemas de suspensión, se examinan los distintos enfoques, herramientas y aplicaciones en el contexto de la dinámica vehicular. Además, para el modelo de un cuarto de vehículo, ampliamente utilizado en la literatura, se ofrece su desarrollo mediante ecuaciones diferenciales, función de transferencia, y ecuaciones de estado, incluyendo soluciones y simulaciones en Simulink y SimMechanics. En cuanto al control, se revisan las principales estrategias para la suspensión de vehículos y se apuntan aplicaciones en otros campos de la ingeniería.

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“…Bond graphs have been proven effective for the modeling and simulation of multi-domain systems including automotive systems [27][28][29][30][31][32][33][34][35][36][37][38]. This formulation can be used in hydraulics, mechatronics, thermodynamics, and electrical systems.…”

Section: Bond Graph Modeling For Hevsmentioning

confidence: 99%

Modeling and Simulation of Electric and Hybrid Vehicles

2011

Hybrid Electric Vehicles

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Compared to conventional vehicles, there are more electrical components used in electric, hybrid, and fuel cell vehicles, such as electric machines, power electronics, electronic continuously variable transmissions (CVTs), and embedded powertrain controllers [1, 2]. Advanced energy storage devices and energy converters, such as Li-ion batteries, ultracapacitors (UCs), and fuel cells are introduced in the next-generation powertrains. In addition to these electrification components or subsystems, conventional internal combustion engines (ICEs), mechanical systems, and hydraulic systems may still be present. The dynamic interactions among various components and the multidisciplinary nature make it difficult to analyze a newly designed hybrid electric vehicle (HEV). Each of the design parameters must be carefully chosen for better fuel economy, enhanced safety, exceptional drivability, and a competitive dynamic performance -all at a price acceptable to the consumer market. Prototyping and testing each design combination is cumbersome, expensive, and time consuming. Modeling and simulation are indispensable for concept evaluation, prototyping, and analysis of HEVs. This is particularly true when novel hybrid powertrain configurations and controllers are developed.Furthermore, the complexity of new powertrain designs and dependence on embedded software are a cause for concern among automotive research and development efforts. This results in increasing difficulty in predicting interactions among various vehicle components and systems. In such situations, a modeling environment that can model not only components but also embedded software, such as the electronic throttle controller (ETC) software, is needed. Effective diagnosis also presents a challenge. Modeling can play an important role in the diagnostics of the operating components. For example, running an embedded fuel cell model and comparing the actual fuel cell operating variables to those obtained from the model can help fault diagnosis of fuel cells. * © [2007] IEEE. Reprinted, with permission, from the Proceedings of the IEEE. Hybrid Electric Vehicles: Principles and Applications with Practical Perspectives, First Edition.

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Modelling and analysis of an active suspension 1/4 of vehicle with bond graph

Cited by 7 publications

References 1 publication

Trajectory Tracking Control Design of a Mass-Damping-Spring System with Uncertainty using the Bond Graph Approach

Trajectory Tracking Control Design of a Mass-Damping-Spring System with Uncertainty using the Bond Graph Approach

Los Sistemas de Suspensión Activa y Semiactiva: Una Revisión

Modeling and Simulation of Electric and Hybrid Vehicles

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