Andreas Hackl

Extended firefly algorithm for multimodal optimization

Many real world optimization problems have to be treated as multi-objective optimization problems. The Firefly Algorithm (FFA), a stochastic optimization method mimics the behavior of fireflies, which use a kind of flashing light to communicate with other members of their species. FFA is implicitly able to detect good local solutions on its way to the best solution. This disposition is successfully boosted by identifying clusters of fireflies which gather around promising local solutions. Subsequently, the update rules used for finding the new positions of the fireflies are applied among members of the particular clusters only. This extended FFA will be used to solve the well known Rastrigin test function and an electromagnetic field problems, the optimal design of a magneto-rheologic clutch, respectively.

Road friction estimation using Recursive Total Least Squares

Automated vehicles require information on the current road condition, i.e. the tire-road friction coefficient (μ_max) for trajectory planning and braking or steering interventions. Recursive Total Least Squares (RTLS) is used to estimate μ_max only utilizing the information from Electric Power System (EPS) and other sensors installed in production vehicles. A new state α_f/μ_max (front wheel slip angle divided by μ_max) is introduced which is observed by a proposed nonlinear observer. This state serves as a measurement for friction estimation and judge when the estimation result is reliable. The proposed method is verified in IPG CarMaker.

Experimental validation of the Maxwell model for description of transient tyre forces

Modelling and simulation of safety relevant Driver Assistance Systems (DAS) and Vehicle Dynamics Controllers (VDC) which act in standard and limit situations lead to increasing accuracy demands in the description of dynamic reactions of tyre contact forces, e.g. [4], [7]. For that purpose, first-order approaches are widely applied in this field of vehicle dynamics and handling, which originate from Schlippe & Dietrich [13], were modified by Pacejka [10] and later on refined by Rill [11], [12].

Tyre Dynamics: Model Validation and Parameter Identification

The present paper deals with the experimental validation of tyre dynamics approaches as it is widely applied in tyre models for vehicle dynamics and handling. Firstly it gives a brief derivation of two modelling principles regarding the deflection velocity in the considered direction of the tyre’s deformation. This is than followed by a brief description of the performed measurement procedure. From the measurements, a set of model parameters of the considered tyre, depending on different manoeuvre speeds and frequencies, is identified, where no particular fitting parameters for the tyre dynamics are needed. Based on these model parameters, the related dynamic simulations are carried out. The comparisons show that the applied first-order model describes the behaviour quite well within a certain operation range, whereas the second-order approach cannot deliver better results in spite of the longer computational time. However, for investigations within an enlarged frequency range of the steer input and at high slip angles, a more detailed model is recommended.

Experimental validation of different approaches for thermodynamic simulation of passenger car tyres

Due to the intensified integration of simulation and modelling into the development of automotive vehicles and their assistance systems, the expectations of accuracy and computational efficiency in simulation are increasing rapidly. In addition, simulation finds more and more application in the process of vehicle homologation, which were a pure experimental discipline in the past. In any case, not only demands affecting vehicle modelling but also refined tyre modelling become more important. In recent years, with continuing refinement in tyre simulation, the needs for coping with tyre temperatures and the resulting influences on the tyre characteristics have been considered important.

Li-ion battery model performance for automotive drive cycles with current pulse and EIS parameterization

To examine different battery modeling approaches, three equivalent circuit battery model types and two battery model parametrization methods are investigated in this paper. A simple model, consisting an open circuit voltage and a series resistance, is compared with two enhanced approaches. The first enhanced approach includes a Warburg Impedance to capture diffusion and the second adds two parallel RC circuit pairs to capture double layer capacitance and charge transfer resistance effects. The model parameters are determined with either time or frequency domain test data and performance for both parameterization methods are compared. Finally, model accuracy is experimentally evaluated for a matrix of drive cycles and temperature values.

Experimental Validation of Various Temperature Modells for Semi-Physical Tyre Model Approaches

With increasing level of complexity and automation in the area of automotive engineering, the simulation of safety relevant Advanced Driver Assistance Systems (ADAS) leads to increasing accuracy demands in the description of tyre contact forces. In recent years, with improvement in tyre simulation, the needs for coping with tyre temperatures and the resulting changes in tyre characteristics are rising significantly. Therefore, experimental validation of three different temperature model approaches is carried out, discussed and compared in the scope of this article. To investigate or rather evaluate the range of application of the presented approaches in combination with respect of further implementation in semi-physical tyre models, the main focus lies on the a physical parameterisation. Aside from good modelling accuracy, focus is held on computational time and complexity of the parameterisation process. To evaluate this process and discuss the results, measurements from a Hoosier racing tyre 6.0 / 18.0 10 LCO C2000 from an industrial flat test bench are used. Finally the simulation results are compared with the measurement data.

Parametrisation of a Maxwell model for transient tyre forces by means of an extended firefly algorithm

Developing functions for advanced driver assistance systems requires very accurate tyre models, especially for the simulation of transient conditions. In the past, parametrisation of a given tyre model based on measurement data showed shortcomings, and the globally optimal solution obtained did not appear to be plausible. In this article, an optimisation strategy is presented, which is able to find plausible and physically feasible solutions by detecting many local outcomes. The firefly algorithm mimics the natural behaviour of fireflies, which use a kind of flashing light to communicate with other members. An algorithm simulating the intensity of the light of a single firefly, diminishing with increasing distances, is implicitly able to detect local solutions on its way to the best solution in the search space. This implicit clustering feature is stressed by an additional explicit clustering step, where local solutions are stored and terminally processed to obtain a large number of possible solutions. The enhanced firefly algorithm will be first applied to the well-known Rastrigin functions and then to the tyre parametrisation problem. It is shown that the firefly algorithm is qualified to find a high number of optimisation solutions, which is required for plausible parametrisation for the given tyre model.

Enhanced firefly algorithm for optimal design of a disk type magneto-rheologic fluid clutch

A well established firefly algorithm is improved in order to detect as many local solutions of a given objective function as possible with a minimum number of function calls. This is done by stressing the disposition of this algorithm to cluster the fireflies around good local solutions. This enhanced Firefly Algorithm will be applied for the optimal design of a disk type magneto-rheologic fluid clutch and compared with an Evolution Strategy with cluster sensitive recombination.

Estimation of tire road friction during vehicle steering

Tire-road friction coefficient estimation is critical for designing control systems in highly automated and autonomous vehicles to achieve the maximum performance of the vehicle. Approaches presented in the literature considering the tire lateral force Fy and the self-aligning torque Mz show several shortcomings. For example, in [1], a nonlinear observer is designed which is only guaranteed to be stable when the front wheel slip angle αf and the tire-road friction coefficient μmax are both overor underestimated. In [2], a recursive nonlinear least squares method is proposed, where the global minimum depends highly on the initial guess of μmax and αf , which are usually not known very accurately. In [3], a nonlinear robust observer is designed which is only locally stable, and the attraction domain cannot cover the whole working area of the tires. All of the above methods cannot solve or prove the stability or convergence problem well. In addition, no knowledge on the required dynamical excitation to deliver reliable estimates of μmax can be given since the slope in the quasi-linear region of the lateral tire forces vs. the wheel slip angle is nearly independent of μmax. The present work tries to solve the stability problem by introducing a nonlinear observer with the state