Hierarchical optimisation of the design parameters of a vehicle suspension system

This paper presents a design methodology for the mechanical systems entitled First Design. It is based on a hierarchical organisation of the design, taking into account the notion of robustness at an early phase of the project. The aim is to improve the quality of the system in order to make it robust, less sensitive to the variability of the external parameters and design parameters. We distinguish two main stages of the design cycle: one concerning functional parameters and another concerning physical parameters. The methodology is based on simplified models, on sensitivity analysis and on robust multi-objective optimisation. As an example, the methodology will be applied to the optimisation of vehicle suspension system design parameters. For each stage of the hierarchical design, adapted simplified models, sensitivity analyses and optimisation processes will be studied and applied to our vehicle suspension system.     

Robust design of a passive linear quarter car suspension system using a multi-objective evolutionary algorithm and analytical robustness indexes

This paper deals with the robust design of a passive vehicle suspension system. A robust design methodology based on a multi-objective evolutionary algorithm (MOEA) is used to handle the trade-off between the considered conflicting performance requirements under uncertainty and feasibility constraints. A constrained multi-objective optimisation problem is formulated and the notion of Pareto-optimality is used to increase the quality of the candidate design solutions obtained at each generation by the MOEA. To save computation time, a simplified physical model (quarter car) is considered and the optimisation is performed in the frequency domain, using relevant transmissibilities of the system. The robustness is directly investigated by means of analytical robustness indexes. Time-consuming a posteriori methods, like designs of experiments or Monte Carlo analysis, are therefore avoided. A set of non-dominated solutions is obtained. Thus the designer not only selects a special design, in accordance with the wanted vehicle configuration, but also includes the robustness of each performance requirement in his final decision.     

Multiobjective optimisation of bogie suspension to boost speed on curves

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. The vehicle model has 50 degrees of freedom and is developed in multibody dynamics software SIMPACK. Track shift force, running stability, and risk of derailment are selected as safety objective functions. The improved maximum admissible speeds of the vehicle on curves are determined based on the track plane accelerations up to 1.5?m/s². To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm (GA) and MATLAB/SIMPACK co-simulation is executed at three levels. The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems.     

Wear/comfort Pareto optimisation of bogie suspension

Pareto optimisation of bogie suspension components is considered for a 50 degrees of freedom railway vehicle model to reduce wheel/rail contact wear and improve passenger ride comfort. Several operational scenarios including tracks with different curve radii ranging from very small radii up to straight tracks are considered for the analysis. In each case, the maximum admissible speed is applied to the vehicle. Design parameters are categorised into two levels and the wear/comfort Pareto optimisation is accordingly accomplished in a multistep manner to improve the computational efficiency. The genetic algorithm (GA) is employed to perform the multi-objective optimisation. Two suspension system configurations are considered, a symmetric and an asymmetric in which the primary or secondary suspension elements on the right- and left-hand sides of the vehicle are not the same. It is shown that the vehicle performance on curves can be significantly improved using the asymmetric suspension configuration. The Pareto-optimised values of the design parameters achieved here guarantee wear reduction and comfort improvement for railway vehicles and can also be utilised in developing the reference vehicle models for design of bogie active suspension systems.     

Optimal selection of suspension parameters in large scale vehicle models

Optimum values are selected for the suspension damping and stiffness parameters of complex car models, subjected to road excitation, by applying suitable numerical methodologies. These models result from a detailed finite-element discretisation and possess a relatively large number of degrees of freedom. They also involve strongly nonlinear characteristics, due mostly to large rigid body rotation of some of their components and the properties of the connection elements. First, attention is focused on gaining some insight into the dynamics of the mechanical models examined, resulting when the vehicle passes over roads involving typical geometric profiles. Then, the emphasis is shifted to presenting results obtained by applying appropriate optimisation methodologies. For this purpose, three classes of design criteria are first set up, referring to passenger ride comfort, suspension travel and car road holding and yielding the most important suspension stiffness and damping parameters. Originally, the optimisation is performed by forming a composite cost function and employing a single-objective optimisation method. Since the design criteria are conflicting, a multi-objective optimisation methodology is also set up and applied subsequently.     

Hierarchical optimisation on scissor seat suspension characteristic and structure

Scissor seat suspension has been applied widely to attenuate the cab vibrations of commercial vehicles, while its design generally needs a trade-off between the seat acceleration and suspension travel, which creates a typical optimisation issue. A complexity for this issue is that the optimal dynamics parameters are not easy to approach solutions fast and unequivocally. Hence, the hierarchical optimisation on scissor seat suspension characteristic and structure is proposed, providing a top-down methodology with the globally optimal and fast convergent solutions to compromise these design contradictions. In details, a characteristic-oriented non-parametric dynamics model of the scissor seat suspension is formulated firstly via databases, describing its vertical dynamics accurately. Then, the ideal vertical stiffness-damping characteristic is cascaded via the characteristic-oriented model, and the structure parameters are optimised in accordance with a structure-oriented multi-body dynamics model of the scissor seat suspension. Eventually, the seat effective amplitude transmissibility factor, suspension travel and the CPU time for solving are evaluated. The results show the seat suspension performance and convergent speed of the globally optimal solutions are improved well. Hence, the proposed hierarchical optimisation methodology regarding characteristic and structure of the scissor seat suspension is promising for its virtual development.     

Possible experimental method to determine the suspension parameters in a simplified model of a passenger car

Currently, as well as in the past, researchers have shown great interest in developing suspension systems for vehicles and especially in the design and optimization of the suspension parameters, such as the stiffness and the damping coefficient. These parameters are considered to be important factors that have an influence on safety and improve the comfort of the passengers in the vehicle. This paper describes a simplified methodology to determine, in a quick manner, the suspension parameters for different types of passenger cars equipped with passive suspension systems. Currently, different types of passenger cars are produced with different types of suspension systems. Finding a simplified methodology to determine these parameters with sufficient accuracy would contribute a simplified and quick method to the inspection of the working conditions of a suspension system. Therefore, a simple system to determine these parameters is needed. An analysis of the suspension parameters is performed using mathematical modeling and numerical analysis conducted using the Working Model software. The result derived from the developed methodology shows small errors when compared with the generic values, and it can be concluded that the design of the suspension parameter measurement device using the developed methodology is useful, simple, and has sufficient accuracy.     

Robustness analysis of bogie suspension components Pareto optimised values

Bogie suspension system of high speed trains can significantly affect vehicle performance. Multiobjective optimisation problems are often formulated and solved to find the Pareto optimised values of the suspension components and improve cost efficiency in railway operations from different perspectives. Uncertainties in the design parameters of suspension system can negatively influence the dynamics behaviour of railway vehicles. In this regard, robustness analysis of a bogie dynamics response with respect to uncertainties in the suspension design parameters is considered. A one-car railway vehicle model with 50 degrees of freedom and wear/comfort Pareto optimised values of bogie suspension components is chosen for the analysis. Longitudinal and lateral primary stiffnesses, longitudinal and vertical secondary stiffnesses, as well as yaw damping are considered as five design parameters. The effects of parameter uncertainties on wear, ride comfort, track shift force, stability, and risk of derailment are studied by varying the design parameters around their respective Pareto optimised values according to a lognormal distribution with different coefficient of variations (COVs). The robustness analysis is carried out based on the maximum entropy concept. The multiplicative dimensional reduction method is utilised to simplify the calculation of fractional moments and improve the computational efficiency. The results showed that the dynamics response of the vehicle with wear/comfort Pareto optimised values of bogie suspension is robust against uncertainties in the design parameters and the probability of failure is small for parameter uncertainties with COV up to 0.1.     

Linear matrix inequality based control of vehicle active suspension system

Linear matrix inequality (LMI) methods, novel techniques in solving optimisation problems, were introduced as a unified approach for vehicle's active suspension system controller design. LMI methods were used to provide improved and computationally efficient controller design techniques. The active suspension problem was formulated as a standard convex optimisation problem involving LMI constraints that can be solved efficiently using recently developed interior point optimisation methods. An LMI based controller for a vehicle system was developed. The controller design process involved setting up an optimisation problem with matrix inequality constraints. These LMI constraints were derived for a vehicle suspension system. The resulting LMI controller was then tested on a quarter-car model using computer simulations. The LMI controller results were compared with an optimal PID controller design solution. The LMI controller was further tested by incorporating a nonlinear term in the vehicle's suspension model; the LMI's controller degraded response was enhanced by using gain-scheduling techniques. The LMI controller with gain-scheduling gave good results in spite of the unmodelled dynamics in the suspension system, which was triggered by large deflections due to off-road driving.     

Robust design optimization of suspension system by using target cascading method

This study presents the robust design optimization process of suspension system for improving vehicle dynamic performance (ride comfort, handling stability). The proposed design method is so called target cascading method where the design target of the system is cascaded from a vehicle level to a suspension system level. To formalize the proposed method in the view of design process, the design problem structure of suspension system is defined as a (hierarchical) multilevel design optimization, and the design problem for each level is solved using the robust design optimization technique based on a meta-model. Then, In order to verify the proposed design concept, it designed suspension system. For the vehicle level, 44 random variables with 3% of coefficient of variance (COV) were selected and the proposed design process solved the problem by using only 88 exact analyses that included 49 analyses for the initial meta-model and 39 analyses for SAO. For the suspension level, 54 random variables with 10% of COV were selected and the optimal designs solved the problem by using only 168 exact analyses for the front suspension system. Furthermore, 73 random variables with 10% of COV were selected and optimal designs solved the problem by using only 252 exact analyses for the rear suspension system. In order to compare the vehicle dynamic performance between the optimal design model and the initial design model, the ride comfort and the handling stability was analyzed and found to be improved by 16% and by 37%, respectively. This result proves that the suggested design method of suspension system is effective and systematic.     

Hybrid modelling and damping collaborative optimisation of Five-suspensions for coupling driver-seat-cab system

For the complex structure and vibration characteristics of coupling driver-seat-cab system of trucks, there is no damping optimisation theory for its suspensions at present, which seriously restricts the improvement of vehicle ride comfort. Thus, in this paper, the seat suspension was regarded as ‘the fifth suspension’ of cab, the ‘Five-suspensions’ for this system was proposed. Based on this, using the mechanism modelling method, a 4 degree-of-freedom coupling driver-seat-cab system model was presented; then, by the tested cab suspensions excitation and seat acceleration response, its parameters identification mathematical model was established. Based on this, taking optimal ride comfort as target, its damping collaborative optimisation mathematical model was built. Combining the tested signals and a simulation model with the mathematical models of parameters identification and damping collaborative optimisation, a complete flow of hybrid modelling and damping collaborative optimisation of Five-suspensions was presented. With a practical example of seat and cab system, the damping parameters were optimised and validated by simulation and bench test. The results show that the model and method proposed are correct and reliable, providing a valuable reference for the design of seat suspension and cab suspensions.     

A design methodology for mechatronic vehicles: application of multidisciplinary optimization, multibody dynamics and genetic algorithms

A design methodology for mechatronic vehicles is presented. With multidisciplinary optimization (MDO) methods, strongly coupled mechanical, control and other subsystems are integrated as a synergistic vehicle system. With genetic algorithms (GAs) at the system level, the mechanical, control and other relevant parameters can be optimized simultaneously. To demonstrate the feasibility and efficacy of the proposed design methodology for mechatronic vehicles, it is used to resolve the conflicting requirements for ride comfort, suspension working spaces and unsprung mass dynamic loads in the optimization of half-vehicle models with active suspensions. Both deterministic and random road excitations, both rigid and flexible vehicle bodies and both perfect measurement of full state variables and estimated limited state variables are considered. Numerical results show that the optimized vehicle systems based on the methodology have better overall performance than those using the linear quadratic Gaussian (LQG) controller. It is shown that the methodology is suitable for complex design optimization problems where: (1) there is interaction between different disciplines or subsystems; (2) there are multiple design criteria; (3) there are multiple local optima; (4) there is no need for sensitivity analysis for the optimizer at the system level; and (5) there are multiple design variables.     

A design methodology for mechatronic vehicles: application of multidisciplinary optimization,multibody dynamics and genetic algorithms

A design methodology for mechatronic vehicles is presented. With multidisciplinary optimization (MDO) methods, strongly coupled mechanical, control and other subsystems are integrated as a synergistic vehicle system. With genetic algorithms (GAs) at the system level, the mechanical, control and other relevant parameters can be optimized simultaneously. To demonstrate the feasibility and efficacy of the proposed design methodology for mechatronic vehicles, it is used to resolve the conflicting requirements for ride comfort, suspension working spaces and unsprung mass dynamic loads in the optimization of half-vehicle models with active suspensions. Both deterministic and random road excitations, both rigid and flexible vehicle bodies and both perfect measurement of full state variables and estimated limited state variables are considered. Numerical results show that the optimized vehicle systems based on the methodology have better overall performance than those using the linear quadratic Gaussian (LQG) controller. It is shown that the methodology is suitable for complex design optimization problems where: (1) there is interaction between different disciplines or subsystems; (2) there are multiple design criteria; (3) there are multiple local optima; (4) there is no need for sensitivity analysis for the optimizer at the system level; and (5) there are multiple design variables.     

Parameters optimisation of a vehicle suspension system using a particle swarm optimisation algorithm

The purpose of this paper is to determine the lumped suspension parameters that minimise a multi-objective function in a vehicle model under different standard PSD road profiles. This optimisation tries to meet the rms vertical acceleration weighted limits for human sensitivity curves from ISO 2631 [ISO-2631: guide for evaluation of human exposure to whole-body vibration. Europe; 1997] at the driver's seat, the road holding capability and the suspension working space. The vehicle is modelled in the frequency domain using eight degrees of freedom under a random road profile. The particle swarm optimisation and sequential quadratic programming algorithms are used to obtain the suspension optimal parameters in different road profile and vehicle velocity conditions. A sensitivity analysis is performed using the obtained results and, in Class G road profile, the seat damping has the major influence on the minimisation of the multi-objective function. The influence of vehicle parameters in vibration attenuation is analysed and it is concluded that the front suspension stiffness should be less stiff than the rear ones when the driver's seat relative position is located forward the centre of gravity of the car body. Graphs and tables for the behaviour of suspension parameters related to road classes, used algorithms and velocities are presented to illustrate the results. In Class A road profile it was possible to find optimal parameters within the boundaries of the design variables that resulted in acceptable values for the comfort, road holding and suspension working space.     

Adaptive impedance control of a hydraulic suspension system using particle swarm optimisation

This paper presents a novel active control approach for a hydraulic suspension system subject to road disturbances. A novel impedance model is used as a model reference in a particular robust adaptive control which is applied for the first time to the hydraulic suspension system. A scheme is introduced for selecting the impedance parameters. The impedance model prescribes a desired behaviour of the active suspension system in a wide range of different road conditions. Moreover, performance of the control system is improved by applying a particle swarm optimisation algorithm for optimising control design parameters. Design of the control system consists of two interior loops. The inner loop is a force control of the hydraulic actuator, while the outer loop is a robust model reference adaptive control (MRAC). This type of MRAC has been applied for uncertain linear systems. As another novelty, despite nonlinearity of the hydraulic actuator, the suspension system and the force loop together are presented as an uncertain linear system to the MRAC. The proposed control method is simulated on a quarter-car model. Simulation results show effectiveness of the method.     

Optimisation of lateral car dynamics taking into account parameter uncertainties

Simulation studies on an active all-wheel-steering car show that disturbance of vehicle parameters have high influence on lateral car dynamics. This motivates the need of robust design against such parameter uncertainties. A specific parametrisation is established combining deterministic, velocity-dependent steering control parameters with partly uncertain, velocity-independent vehicle parameters for simultaneous use in a numerical optimisation process. Model-based objectives are formulated and summarised in a multi-objective optimisation problem where especially the lateral steady-state behaviour is improved by an adaption strategy based on measurable uncertainties. The normally distributed uncertainties are generated by optimal Latin hypercube sampling and a response surface based strategy helps to cut down time consuming model evaluations which offers the possibility to use a genetic optimisation algorithm. Optimisation results are discussed in different criterion spaces and the achieved improvements confirm the validity of the proposed procedure.     

Motorcycle suspension design using matrix inequalities and passivity constraints

This paper presents a design methodology for the suspension system of a novel aerodynamically efficient motorcycle. Since the machine’s layout and the rider’s seating position are unconventional, several aspects of the machine design, including the suspension, must be reviewed afresh. The design process is based on matrix inequalities that are used to optimise a road-grip objective function – others could be used equally well. The design problem is cast as the minimisation of an H ₂ cost with passivity constraints imposed on the suspension transference. The resulting bilinear matrix inequality problem is solved using a locally optimal iterative algorithm. The matrix inequality-type characterisation of positive real functions permits the optimisation of the suspension system over an entire class of passive admittances. Torsional springs, dampers and inerters are then used to construct networks corresponding to the optimal (positive real) admittances. Networks of first, second, third and fourth orders are considered, and an argument based on the compromise between complexity and improved grip is made for the most suitable suspension configuration. Finally, the effects of improved road grip on the stability of the vehicle’s lateral dynamics are analysed.     

Multi-objective optimization of quarter-car models with a passive or semi-active suspension system

A systematic methodology is applied in an effort to select optimum values for the suspension damping and stiffness parameters of two degrees of freedom quarter-car models, subjected to road excitation. First, models involving passive suspension dampers with constant or dual rate characteristics are considered. In addition, models with semi-active suspensions are also examined. Moreover, special emphasis is put in modeling possible temporary separations of the wheel from the ground. For all these models, appropriate methodologies are employed for capturing the motions of the vehicle resulting from passing with a constant horizontal speed over roads involving an isolated or a distributed geometric irregularity. The optimization process is based on three suitable performance criteria, related to ride comfort, suspension travel and road holding of the vehicle and yielding the most important suspension stiffness and damping parameters. As these criteria are conflicting, a suitable multi-objective optimization methodology is set up and applied. As a result, a series of diagrams with typical numerical results are presented and compared in both the corresponding objective spaces (in the form of classical Pareto fronts) and parameter spaces.     

Multi-objective optimization of quarter-car models with a passive or semi-active suspension system

A systematic methodology is applied in an effort to select optimum values for the suspension damping and stiffness parameters of two degrees of freedom quarter-car models, subjected to road excitation. First, models involving passive suspension dampers with constant or dual rate characteristics are considered. In addition, models with semi-active suspensions are also examined. Moreover, special emphasis is put in modeling possible temporary separations of the wheel from the ground. For all these models, appropriate methodologies are employed for capturing the motions of the vehicle resulting from passing with a constant horizontal speed over roads involving an isolated or a distributed geometric irregularity. The optimization process is based on three suitable performance criteria, related to ride comfort, suspension travel and road holding of the vehicle and yielding the most important suspension stiffness and damping parameters. As these criteria are conflicting, a suitable multi-objective optimization methodology is set up and applied. As a result, a series of diagrams with typical numerical results are presented and compared in both the corresponding objective spaces (in the form of classical Pareto fronts) and parameter spaces.     

Pareto optimisation of railway bogie suspension damping to enhance safety and comfort

This paper presents the optimisation of damping characteristics in bogie suspensions using a multi-objective optimisation methodology. The damping is investigated and optimised in terms of the resulting performances of a railway vehicle with respect to safety, comfort and wear considerations. A complete multi-body system model describing the railway vehicle dynamics is implemented in commercial software Gensys and used in the optimisation. In complementary optimisation analyses, a reduced and linearised model describing the bogie system dynamics is also utilised. Pareto fronts with respect to safety, comfort and wear objectives are obtained, showing the trade-off behaviour between the objectives. Such trade-off curves are of importance, especially in the design of damping functional components. The results demonstrate that the developed methodology can successfully be used for multi-objective investigations of a railway vehicle within models of different levels of complexity. By introducing optimised passive damping elements in the bogie suspensions, both safety and comfort are improved. In particular, it is noted that the use of optimised passive damping elements can allow for higher train speeds. Finally, adaptive strategies for switching damping parameters with respect to different ride conditions are outlined and discussed.