Optimisation of Double Wishbone Suspension System Using Multi-Objective Genetic Algorithm

Arikere, Adithya; Kumar, Girish; Bandyopadhyay, Sandipan

doi:10.1007/978-3-642-17298-4_48

Cited by 10 publications

(8 citation statements)

References 11 publications

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“…Xiaohai Wang et al introduced the restricted mutation generation area into the GA, which increased the search ability of the algorithm near the optimal path in the later stage, shortened the planning time and improved the feasibility of the algorithm [9]. A. Arikere et al used multi-objective genetic algorithm to search the optimal solution of the double wishbone design problem [10]. Yubing Wang et al proposed a distributed PSO algorithm for fast convergence, random cross-search and accurate search to avoid falling into local optimization and improve algorithm performance [11].…”

Section: Introductionmentioning

confidence: 99%

Path planning of patrol robot based on modified grey wolf optimizer

Zhang

Ning

Li³

et al. 2023

Robotica

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The grey wolf optimizer (GWO) as a new intelligent optimization algorithm has been successfully applied in many fields because of its simple structure, few adjustment parameters and easy implementation. This paper mainly aims at the defects of GWO in path planning application, such as easily falling into local optimization, poor convergence and poor accuracy, and turn point grey wolf optimization (TPGWO) algorithm is proposed. First, the idea of cross-mutation and roulette is used to increase the initial population of GWO and improve the search range. At the same time, the convergence factor function is improved to become a nonlinear update. In the early stage, the search range is expanded, and in the later stage, the convergence speed is increased, while the parameters in the convergence factor function can be adjusted according to the number of obstacles and the map area to change the turning point of the function to improve the convergence speed and accuracy of the algorithm. The turning times and turning angles of the obtained path are added to the fitness function as penalty values to improve the path accuracy. The optimization test is carried out through 16 test functions, and the test results prove the convergence and robustness of TPGWO algorithm. Finally, the TPGWO algorithm is applied to the path planning of patrol robot for simulation experiments. Compared with the GWO algorithm and Particle Swarm Optimization, the simulation results show that the TPGWO algorithm has better convergence, stability and accuracy in the path planning of patrol robot.

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Section: Introductionmentioning

confidence: 99%

Path planning of patrol robot based on modified grey wolf optimizer

Zhang

Ning

Li³

et al. 2023

Robotica

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“…As a result, the mathematical relationship of the key points required for the wheel space position is obtained through derivation. If the movement of the lower swing arm is used as the system input to change the suspension mechanism, the position of each key point of the suspension system at any time can be solved by the above equations (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), and then it can express the front wheel alignment parameters of the car suspension kinematics.…”

Section: Kinematics Analysis Of Double Wishbone Suspension and Analyt...mentioning

confidence: 99%

“…Taking the minimum deviation of the toe angle and steering angle during the wheel jump stroke period as the design goal, the position of optimal connecting rod hard point was determined, and the maximum steering error of the system was reduced to 89.6%. Arikere et al 10 deduced the spatial kinematics mathematical model of the double wishbone suspension, and suspension, and applied multi-objective planning to the design of the automobile suspension system, and in the process of wheel jump up and down, the optimization goal is to reduce the change amount of toe angle and camber angle, and obtain the non-inferior solution set of the optimization model based on the NSGA-II algorithm to improve the handling stability. Hengmin Qi et al 11 presented a comprehensive tune in terms of vehicle coupled roll and lateral dynamics by adjusting the parameters of HIS system.…”

Section: Introductionmentioning

confidence: 99%

Analysis and optimization of vehicle handling stability with considering front and rear suspension hard point coordinates

Gao

Han

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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For the front double wishbone suspension, starting from the space analytic geometry, a method of describing the movement law of the its is proposed and kinematic analysis is performed, and then the expressions of front wheel alignment parameters are derived by the vector method. Based on the theory of space coordinate transformation, a method of analyzing the kinematics of the five-link suspension is proposed, and the toe angle and camber angle of the rear wheels are derived. The virtual kingpin of the rear suspension is approximated by the instant screw axis method to obtain the expressions of the kingpin alignment parameters. The sensitivity analysis of the impact of the hard point coordinates on the suspension performance indicators is obtained, and the hard point coordinates that are most sensitive to the front and rear suspension performance indicators are obtained. And this is used as the analysis object to explore the influence of the hard point coordinate changes on the wheel alignment parameters. The frequency response index of the vehicle is derived from the vehicle dynamics model, and the change law of the frequency response index of the vehicle in the low and high frequencies is obtained based on swept-sine input simulation. Finally, the sensitivity analysis of the vehicle handling stability is carried out on the hard point coordinates, and the more sensitive hard point coordinates are selected as the optimization variables. The vehicle frequency characteristic index is used as the optimization target, and the NSGA-II algorithm is used for multi-objective optimization. After optimization, the result shows that the handing stability of the vehicle in the low frequency range has been improved.

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“…A substantial amount of literature also exists on the design and analysis of the more commonly used double-wishbone suspension (also known as the AA suspension), and of its short–long A (SLA) version, as well as on the kinematic synthesis of the corresponding RSSR-SS and RSSR-RRS linkages. 91–115 Other than their traditional application to passenger cars, 116–121 double-wishbone suspensions have found increasing use in motor coaches, trucks, agricultural tractors, and off-road vehicles. 115, 122–125 There are also reports on three-link suspension configurations that depart from what it is commonly assumed to be a double-wishbone mechanism, 129–131 which are also termed multi-link suspensions.…”

Section: Introductionmentioning

confidence: 99%

“…Some of the above-cited papers report on the design of multi-link 40, 57, 58 and double- wishbone 100, 103, 105, 106, 107, 109 front-suspension mechanisms through repeated analysis and the use of simulation software or computer algebra systems. Graphical 1–5,10–12 , analytical and numerical approaches 26, 48, 50, 56, 97, 101, 102, 113 to five-link, four-link, and three-link front suspension kinematic synthesis are available to the interested reader, but these methods appear to be difficult to implement and are rarely accompanied by clearly illustrated numerical examples.…”

Section: Introductionmentioning

confidence: 99%

A unified approach to the kinematic synthesis of five-link, four-link, and double-wishbone suspension mechanisms with rack-and-pinion steering control

Simionescu

2016

Proceedings of the Institution of Mechanical Engineers, Part D:

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This paper presents a unified approach to the problem of dimensional synthesis of the five-link, four-link, and three-link (double-wishbone) suspension mechanisms with a rack-and-pinion steering input. In a simplified approach, the guiding links are assumed to be removed from their joints, allowing the wheel to be exactly driven through a number of prescribed jounce–rebound and steering positions during the kinematic synthesis process. Alternatively, the tie rod is maintained in place, and the rack length and the lengths of the remaining four guiding links are allowed to vary. An optimization problem based on the aggregated change in distance between the released ball joints evaluated in the aforementioned positions is then defined. By prescribing to the wheel a jounce–rebound motion only, rear-suspension mechanisms of the five-link, four-link, and three-link types can be conveniently synthesized by following the same procedure. Several solutions obtained through synthesis are then analyzed for their changes in steering error, recessional wheel motion, wheel track, toe angle and camber angle, showing very promising results. Additionally, a comprehensive review of nearly 150 publications relevant to the suspension design of automobiles is provided in the paper.

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Optimisation of Double Wishbone Suspension System Using Multi-Objective Genetic Algorithm

Cited by 10 publications

References 11 publications

Path planning of patrol robot based on modified grey wolf optimizer

Path planning of patrol robot based on modified grey wolf optimizer

Analysis and optimization of vehicle handling stability with considering front and rear suspension hard point coordinates

A unified approach to the kinematic synthesis of five-link, four-link, and double-wishbone suspension mechanisms with rack-and-pinion steering control

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