Study on effect of abs control system to the vehicle dynamic behavior during braking on various speed and road condition

The vehicle safety system is divided into two groups that are passive safety and active safety system. While a passive safety system’s purpose is to protect the occupant during an accident, an active safety system’s goal is to enable the vehicle to be controlled to avoid any collision. The passive safety system is a seatbelt, airbag, headrest, etc. Anti-lock Braking System (ABS) is one of many systems under the active safety system, a basic skid control system that can prevent the tire from locking up and enable the vehicle to steer during braking. Another active system is Forward Collision Warning (FCW), Electronic Stability Control (ESC), etc. Even with an active safety system, especially during emergency braking, the vehicle dynamic behavior may change abruptly, which can cause the vehicle to become unstable. The incident may be worse during emergency braking on the wet road condition. This study focuses on analyzing the vehicle dynamic behavior during emergency braking without and with ABS enabled in the system on dry and wet road conditions. The analysis of this study is divided into three phases; to investigate the vehicle dynamic behavior of the UMP test car (Proton Persona) during the braking experiment without ABS, development of the mathematical model of the vehicle and validation with the experimental result, and analyses of the simulation model with implementation of ABS. From the experimental results, on dry road conditions, all experiments conducted from an initial speed of 30 km/h, 50 km/h, and 60 km/h show no locking up occurred. While on wet road conditions, the lock-up condition is shown at front tires starting from the experiment at an initial speed of 50 km/h and 60 km/h. From experimental data, the mathematical model is simulated inside Matlab Simulink, and the model validation using RMSE is all under 10 % for vehicle speed, tire speed, stopping distance and slip ratio. With the addition of ABS inside the model, the simulation was repeated. Only on wet road condition is re-performed as on dry road condition there is no lock-up occur. With ABS enabled in the simulation, it is shown that the speed of all tires decreased gradually and no lock-up occurred. Thus, showing the modelling stay or lower than the optimum range of slip ratio used in the ABS. Additionally, the friction coefficient between the tire and the road was high, meaning the vehicle could be steered properly during braking. Data also shows shorter in both stopping time and stopping distance. The vertical forces also reduce periodically, showing the increase of vehicle stability. Furthermore, with the development of the mathematical model in this research, various ABS algorithms to improve the effectiveness of ABS on the vehicle can be done in future studies

Discrete-time slip control algorithms for a hybrid electric vehicle

This thesis develops a discrete-time sliding mode control scheme for a slip control of a hybrid electric vehicle. In order to handle different road conditions, fuzzy logic technique is employed to develop control of slip ratio. A discrete-time Sliding mode observer is also designed to estimate the vehicle velocity online. Furthermore, in order to cope up with changing slip dynamic for varying road conditions an Adaptive sliding mode control has been designed by employing Lyapunov theory. The performances of developed adaptive sliding mode control, Sliding mode control and Fuzzy logic control for slip ratio are compared through extensive Matlab simulation and it is observed that the discrete time Fuzzy adaptive sliding mode control perform effectively

Fault-Tolerant Aircraft Control Based on Self-Constructing Fuzzy Neural Networks and Multivariable SMC under Actuator Faults

This paper presents a fault-tolerant aircraft control (FTAC) scheme against actuator faults. Firstly, the upper bounds of the norms of the unknown functions are introduced, which contain actuator faults and model uncertainties. Subsequently, self-constructing fuzzy neural networks (SCFNNs) with adaptive laws are capable of obtaining the bounds. The bound estimation can reduce the computational burden with a lower amount of rules and weights, rather than the dynamic matrix approximation. Moreover, with the aid of SCFNNs, a multivariable sliding mode control (SMC) is developed to guarantee the finite-time stability of the handicapped aircraft. As compared to the existing intelligent FTAC techniques, the proposed method has twofold merits: fault accommodation can be promptly accomplished and decoupled difficulties can be overcome. Finally, simulation results from the nonlinear longitudinal Boeing 747 aircraft model illustrate the capability of the presented FTAC scheme

Research and Implement of PMSM Regenerative Braking Control for Electric Vehicle

As the society pays more and more attention to the environment pollution and energy crisis, the electric vehicle (EV) development also entered in a new era. With the development of motor speed control technology and the improvement of motor performance, although the dynamic performance and economical cost of EVs are both better than the internal-combustion engine vehicle (ICEV), the driving range limit and charging station distribution are two major problems which limit the popularization of EVs. In order to extend driving range for EVs, regenerative braking (RB) emerges which is able to recover energy during the braking process to improve the energy efficiency. This thesis aims to investigate the RB based pure electric braking system and its implementation. There are many forms of RB system such as fully electrified braking system and blended braking system (BBS) which is equipped both electric RB system and hydraulic braking (HB) system. In this thesis the main research objective is the RB based fully electrified braking system, however, RB system cannot satisfy all braking situation only by itself. Because the regenerating electromagnetic torque may be too small to meet the braking intention of the driver when the vehicle speed is very low and the regenerating electromagnetic torque may be not enough to stop the vehicle as soon as possible in the case of emergency braking. So, in order to ensure braking safety and braking performance, braking torque should be provided with different forms regarding different braking situation and different braking intention. In this thesis, braking torque is classified into three types. First one is normal reverse current braking when the vehicle speed is too low to have enough RB torque. Second one is RB torque which could recover kinetic energy by regenerating electricity and collecting electric energy into battery packs. The last braking situation is emergency where the braking torque is provided by motor plugging braking based on the optimal slip ratio braking control strategy. Considering two indicators of the RB system which are regenerative efficiency and braking safety, a trade-off point should be found and the corresponding control strategy should be designed. In this thesis, the maximum regenerative efficiency is obtained by a braking torque distribution strategy between front wheel and rear wheel based on a maximum available RB torque estimation method and ECE-R13 regulation. And the emergency braking performance is ensured by a novel fractional-order integral sliding mode control (FOISMC) and numerical simulations show that the control performance is better than the conventional sliding mode controller

Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation

In this research, the improved mass spring model is presented to simulate the human liver deformation. The underlying MSM is redesigned where fuzzy knowledge-based approaches are implemented to determine the stiffness values. Results show that fuzzy approaches are in very good agreement to the benchmark model. The novelty of this research is that for liver deformation in particular, no specific contributions in the literature exist reporting on real-time knowledge-based fuzzy MSM for liver deformation

Experimental and numerical approach to investigate tire and ABS combined influence on wet braking performance of passenger cars.

This PhD activity is mainly focused on the study of the emergency braking test, where the tire behaviour can be influenced by the ABS system during such manoeuvre on wet roads. The main goal is to investigate and optimize the optimal shape of the longitudinal force characteristics of the tire in order to reduce the braking distance. The only evaluation of the μ-peak could not be sufficient for reliable assessments but the whole shape of the longitudinal curve should be considered. Nowadays, the Wet Grip Index (WGI) is the parameter with which it is possible to classify the quality of a tire in wet conditions in the EU tire label and it is mainly based on maximum grip that a tire can perform interacting with the wet road. Understanding the optimal shape of the curve could also mean to understand if the WGI approach can give a complete evaluation of tire performance during the braking, or there could be something more to take into account. A numerical approach was considered and a ABS logic has been modelled with the aim to replicate the fundamental strategies of a passenger car. A half vehicle model has been considered for this research work. A more physical approach on ABS modelling is proposed in this thesis, with the aim to estimate the optimal working range of the logic without any pre-set information. Regarding the implemented tire model, the focuses were on trying to find a method to characterize the tire in wet conditions and understand how the longitudinal relaxation length can influence the ABS work in simulation environment. A method is proposed to get a possible estimation of the longitudinal relaxation length of the tire from vehicle measurements. Moreover, a study about the relaxation length evaluation with respect to the excitation frequency coming from the longitudinal slippage will be described in this thesis. The emergency braking model was used to optimize the reference curve in order to reduce the braking distance. The analysis is focused on three parameters that can identify the longitudinal characteristics of the tire: the braking stiffness, μ-peak and drop down of the grip after the peak condition. The main outcome of the simulation results shows that the μ-peak could not be considered as the only critical parameter to evaluate the braking performance of the tire and that the drop-down of the grip seems to play a very important role to reduce braking distances

Extremum Seeking Method And Its Applications In Automotive Control

Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2011Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2011Kontrol uygulamalarındaki ana yöntem, ele alınan bir sistemi belli bir çalışma noktasına veya referans yörüngesine oturtmaktır. Fakat bazı kontrol problemlerinde, arzu edilen sistem performansı ile o performansı sağlayacak sistem çalışma noktası arasındaki ilişki önceden bilinmemektedir. Örneğin sistemin çalışma noktası ile çıkışı arasında o şekilde bir ilişki olabilir ki, bu fonksiyonun bir ekstremumu olabilir ve amaç, sistem çıkışını bu ekstremum değere getirecek çalışma noktasının aranması olabilir. Sistemin çalışma noktası ile çıkışı arasındaki fonksiyonun belirsizliği, çıkışı maksimize (veya minimize) edecek çalışma noktasının bulunması için bir uyarlama algoritmasının kullanımını gerekli kılmaktadır. Bu problem Ekstremum Arama Algoritması (EAA) ile çözülebilmektedir. Bu algoritma, sistemin performans fonksiyonunun tamamen veya kısmen bilinmediği, zamanla değişebildiği, sistemin eğrisel olduğu, belirsizlik ve bozucular içerdiği durumlar için uygundur. Örneğin acil durum frenlemesinde ihtiyaç duyulduğu gibi, bilinmeyen yol koşullarında tekerlek ile yol arasındaki teker kuvvetlerinin maksimize edilmesi başa çıkılması gereken zor bir iştir. Yol sürtünme katsayısı genellikle önceden bilinmemektedir ve anlık olarak kestirimi zordur. ABS kontrol algoritması, bilinmeyen yol koşullarında teker frenleme kuvvetini maksimize edecek hidrolik fren basıncının optimum çalışma noktasını bulmalıdır. Optimum çalışma noktası seçimindeki bir yanlış karar, ya olabilecekten daha az frenleme kuvvetinin üretilmesine ya da tekerleklerin kilitlenmesine, böylece aracın kontrol edilebilirliğinin ortadan kalkmasına sebep olacaktır. Minimum durma mesafesi ancak tekerleklerin, tekerlek kuvveti-tekerlek kayma oranı eğrisinde en tepe noktasında çalışmaları durumunda gerçekleşir. Bu durumda tekerleklerin kilitlenmesi engellendiği için aracın yanal kararlılığı ve direksiyon ile yönlendirilebilirliği de iyileşecektir. Tezde önce, optimum tekerlek kayma değeri bilinmeden tekerlek kuvvetinin maksimize edilmesi için, tekerlek modeli parametrelerinin uyarlanması yöntemi ile entegre edilmiş bir Ekstremum Arama Algoritması (EAA) önerilmiştir. Bunun için bir çeyrek araç modeli ele alınmıştır. Literatürdeki çoğu ekstremum arama algoritmaları, optimum çalışma noktasını ararken amaç fonksiyonunun gerçek zamanlı olarak ölçümüne dayanmaktadır. Bu çalışmada önerilen kontrol algoritması, amaç fonksiyonunun anlık ölçümü gereksinimini ortadan kaldırarak onun yerine parametre uyarlamalı analitik bir yöntem geliştirmiştir. Kararlılık ve global maksimum noktasına yakınsama durumları, Lyapunov kararlılık analizi ile gösterilmiştir. Önerilen yaklaşımın etkinliğini göstermek için farklı yol koşullarında simulasyon çalışmaları yapılmıştır. İkinci olarak, boyuna frenleme yanında engelden kaçınma manevrasında olduğu gibi yanal hareketi de gözönüne alan EAA temelli bir ABS kontrol algoritması sunulmuştur. Bu algoritmada, yol sürtünme katsayısını kestirmeye gerek kalmadan, tekerlek ve yol arasındaki optimum kayma oranı anlık olarak aranmaktadır. Literatüre getirilen bir yenilik olarak, “tekerlek kuvveti”-“kayma oranı” karakteristik eğrisi üzerinde tekerleklerin çalışma bölgesini belirlemek için sürücü direksiyon girişi ABS frenleme prosedürüne eklenmiştir. Sadece boyuna frenleme durumunda algoritma, tekerleklerin çalışma bölgesini, kuvvet-kayma eğrisinin tepe noktası yakınında tutmaktadır. Eğer sürücü frenlemeye ek olarak yanal hareket de talep ederse, tekerleklerin çalışma bölgesi otomatik olarak değiştirilmekte ve böylece yanal tekerlek kuvvetleri arttırılarak aracın yanal kararlılığı iyileştirilmektedir. Gerçek bir araçtan alınan ölçümlerle doğrulanmış bir tam araç modeli kullanılarak yapılan simülasyonlar algoritmanın etkinliğini göstermektedir. Üçüncü olarak, bir paralel tip hibrid elektrikli araç (HEA) için enerji yönetimi stratejisi önerilmiştir. HEA’lar, daha verimli, daha az çevreyi kirleten araçlara gereksinim sonucunda geliştirilmiştir. Elektrikli araçlar parlak bir çözüm olsa da şu andaki kısa menzilleri ve uzun batarya şarj süreleri, yaygın kullanımlarını geleceğe ötelemektedir. HEA’lar bu doğrultuda kabul edilebilir bir ara çözüm sunmaktadırlar. Hibrid bir elektrikli araçta, elektrokimyasal bir batarya ile güç verilen bir elektrikli motor (EM), fosil yakıt tarafından güç verilen içten yanmalı motor (İYM) ile birlikte kullanılmaktadır. Bunlar, yakıt tüketimi ve emisyonları azaltmadaki önemli potansiyelleri ile günümüzde en uygulanabilir teknoloji olarak görülmektedirler. Tezde verilen HEA enerji yönetim stratejisinin ana amacı, toplam verimi maksimize ederek yakıt tüketimini iyileştirmek ve bunu yaparken de sürücünün güç isteğini karşılamak, batarya şarj durumunu korumak ve İYM, EM güç kısıtları gibi çeşitli kısıtları göz önüne almaktır. Önerilen enerji yönetimi stratejisinde, ekstremum arama algoritması, toplam verimi maksimize edecek şekilde içten yanmalı motor ve elektrik motoru arasında optimum tork dağılımını belirlemektedir. Kontrol stratejisi üst seviye ve alt seviye olmak üzere iki seviyelidir: Üst seviyedeki karar verme kontrolcüsü aracın hangi modda çalışacağını tespit eder. Bu modlar: İçten yanmalı motor ve elektrik motorunun eşzamanlı çalışması, yalnızca elektrik motoru, yalnızca içten yanmalı motor, veya rejeneratif frenleme modlarıdır. İçten yanmalı motor ve elektrik motorunun eşzamanlı çalışması sırasında, bu iki enerji kaynağı arasındaki optimum enerji dağılımını ekstremum arama algoritması, toplam verimi maksimize edecek şekilde belirlemektedir. Böylece literatürde ilk defa bir ekstremum arama algoritması HEA kontrol problemine uyarlanmıştır. Önerilen kontrol algoritmasının performans değerlendirmesi için ayrıca bir dinamik programlama (DP) çözümü de elde edilmiştir. DP çözümü, ele alınan sürüş çevrimi ve sürüş koşulları için elde edilebilecek minimum yakıt tüketimini hesaplamaktadır. DP prosedürünü uygulamak için, bütün bir sürüş çevrimi ve sürüş koşulları önceden bilinmelidir. Gerçek bir araçta gelecekteki sürüş koşulları bilinmediği için DP gerçek zamanlı bir kontrolcü olarak kullanılamaz. Dinamik programlama çözümü gerçek zamanlı kontrol algoritmasının performansının değerlendirilmesi için kullanılmaktadır. Tezde önerilen kontrol algoritmasının etkinliğini göstermek için gerçekçi bir araç modeli kullanılarak çeşitli sürüş çevrimleri ile simülasyonlar yapılmıştır.The mainstream methodology in control applications is to regulate the considered system to known set points or reference trajectories. However, in some control problems, the relation between the system setpoint and a desired system performance is unknown a priori. One situation is that, the reference-to-output map has an extremum and the objective is to select the set point to keep the output at that extremum value. The uncertainty in the reference-to-output map makes it necessary to use an adaptation method to find the set point which maximizes (or minimizes) the output. This problem can be solved via the Extremum Seeking Algorithm (ESA). The algorithm fits problems that possess completely or partially unknown performance functions that may also change in time or that have nonlinear systems with structured or unstructured uncertainties and disturbances. For example, as needed in an emergency braking case, the maximization of the tire force between the tire contact patch and the road in the presence of unknown road conditions is a challenging task. The road friction coefficient is mostly unknown a priori and it is difficult to estimate it on-line. The ABS control algorithm should find the optimal set point of brake hydraulic pressure, which maximizes the wheel braking force subject to unknown and possibly changing road conditions. A misjudgment about the optimal set point choice may cause lower performance of braking via either less friction force generation or via blocking the tire rotation. The minimum stopping distance is ensured when the tires operate at the peak point of the braking force versus slip characteristic curve subject to unknown road conditions. In addition, lateral stability and steerability are also improved as locking of the wheels is prevented. In this thesis, firstly, an Extremum Seeking Algorithm (ESA) integrated with the adaptation of the tire model parameters is proposed for maximizing braking force without utilizing optimum slip value information. A quarter car vehicle model is considered in this section of the thesis. Most of the commonly used extremum seeking algorithms in the literature search for the optimal operating point in order to maximize or minimize a given cost function which is measured on a real-time basis. The control algorithm introduced in this dissertation removes the on-line cost function measurement requirement and instead, an analytic approach with adaptive parameter tuning is developed along the ESA. Stability and reaching the global maximum operating point of the unknown cost function are proved using Lyapunov stability analysis. Simulation study for ABS control under different road pavement conditions is presented to illustrate the effectiveness of the proposed approach. Secondly, an ABS control algorithm based on ESA is presented for considering lateral motion in addition to the longitudinal emergency braking, such as the obstacle avoidance maneuvers, also. The optimum slip ratio between the tire contact patch and the road is searched online without having to estimate the road friction conditions. This is achieved by adapting the ESA as a self-optimization routine that seeks the peak point of the force-slip curve. As a novel addition to the literature, the proposed algorithm incorporates driver steering input information into the ABS braking procedure to determine the operating region of the tires on the “tire force”-“slip ratio” characteristic curve. The algorithm operates the tires near the peak point of the force-slip curve during straight line braking. When the driver demands lateral motion in addition to braking, the operating regions of the tires are modified automatically, for improving the lateral stability of the vehicle by increasing the tire lateral forces. Simulations with a full vehicle model validated with actual vehicle measurements show the effectiveness of the algorithm. Thirdly, an energy management strategy for a parallel type hybrid electric vehicle (HEV) is proposed. HEVs are developed in the need of more efficient, less polluting vehicles. Electric vehicles seem as a promising solution but for now, their short driving distance combined with the long recharging period for batteries postpones their widespread use to the future. HEVs offer an acceptable, intermediate solution. In a hybrid electric vehicle, an electric motor (EM) powered by an electrochemical battery is used along with the internal combustion engine (ICE) powered by fossil fuel. They appear to be one of the most viable technologies with significant potential to reduce fuel consumption and pollutant emissions. The main objective of the HEV energy management strategy given in the thesis is maximizing the powertrain efficiency and hence improving the fuel consumption while meeting the driver’s power demand, sustaining the battery state of charge and considering constraints such as engine and electric motor power limits. In the proposed energy management strategy, extremum seeking algorithm searches constantly optimum torque distribution between the internal combustion engine and electric motor for maximizing the powertrain efficiency. The control strategy has two levels of operation: the upper and lower levels. The upper level decision making controller chooses the vehicle operation mode such as the simultaneous use of the internal combustion engine and electric motor, use of only the electric motor, use of only the internal combustion engine, or regenerative braking. In the simultaneous use of the internal combustion engine and electric motor, the optimum energy distribution between these two sources of energy is determined via the extremum seeking algorithm that searches for maximum powertrain efficiency. In the literature, this is the first time an extremum seeking algorithm is applied to the HEV control problem. A dynamic programming (DP) solution is also obtained and used to form a benchmark for performance evaluation of the proposed method. DP solution gives the minimum obtainable fuel consumption in a considered driving cycle and driving conditions. In order to apply DP procedure, the whole driving cycle and driving conditions should be known in advance. Since future driving conditions are unknown in a real vehicle, DP cannot be utilized in a real time controller. The dynamic programming solution is used offline for performance evaluation of the real time control algorithm. Detailed simulations with various driving cycles and using a realistic vehicle model are presented to illustrate the effectiveness of the methodology.DoktoraPh