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

A robust super twisting fractional-order sliding mode-based control of vehicle longitudinal dynamic subjected to a constant actuator fault

This paper deals with the design and analysis of a super twisting fractional-order sliding mode controller (ST-FOSMC) to adjust the vehicle longitudinal dynamic when braking. While vehicle loading, road types, and modeling uncertainties are time-varying parameters, the control law must be robust against these disturbances. Also, the aging of the brake plate may introduce a difference between the control output and the actuator response that should be considered. The proposed control strategy has been used to enable the anti-lock braking system (ABS) to track the desired wheel slip value despite the presence of disturbances and constant actuator fault. The design of this controller is presented and the system stability is guaranteed by applying the Lyapunov theory. We carried out a simulation example that makes a comparison between our controller and the one based on the fractional-order sliding mode control to investigate which one of them outperforms the other. The results exhibit the superiority of the super twisting fractional order controller over the traditional fractional-order sliding mode controller during the braking phase

Intelligent control and look-ahead energy management of hybrid electric vehicles

A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved

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

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

Integration of anti-lock braking system and regenerative braking for hybrid/electric vehicles

Vehicle electrification aims at improving energy efficiency and reducing pollutant emissions which creates an opportunity to use the electric machines (EM) as Regenerative Braking System (RBS) to support the friction brake system. Anti-lock Braking System (ABS) is part of the active safety systems that help drivers to stop safely during panic braking while ensuring the vehicle’s stability and steerability. Nevertheless, the RBS is deactivated at a safe (low) deceleration threshold in favour of ABS. This safety margin results in significantly less energy recuperation than what would be possible if both RBS and ABS were able to operate simultaneously. Vehicle energy efficiency can be improved by integrating RBS and friction brakes to enable more frequent energy recuperation activations, especially during high deceleration demands. The main aim of this doctoral research is to design and implement new wheel slip control with torque blending strategies for various vehicle topologies using four, two and one EM. The integration between the two braking actuators will improve the braking performance and energy efficiency of the vehicle. It also enables ABS by pure EM in certain situations where the regenerative brake torque is sufficient. A novelmethod for integrating the wheel slip control and torque blending is developed using Nonlinear Model Predictive Control (NMPC). The method is well known for the optimal performance and enforcement of critical control and state constraints. A linear MPC strategy is also developed for comparison purpose. A pragmatic brake torque blending algorithm using Daisy-Chain with sliding mode slip control is also developed based on a pre-defined energy recuperation priority. Simulation using high fidelity model using co-simulation in Matlab/Simulink and CarMaker is used to validate the developed strategies. Different test patterns are used to evaluate the controllers’ performance which includes longitudinal and lateral motions of the vehicle. Comparison analysis is done for the proposed strategies for each case. The capability for real-time implementation of the MPC controllers is assessed in simulation testing using dSPACE hardware

Intelligent Sliding Mode Scheme for Regenerative Braking Control

Controller design for an Anti-Lock Braking System (ABS) of a Hybrid Electric Vehicle (HEV) or Electric Vehicle (EV) is a challenging task because of the trade-off between braking efficiency and energy recuperation efficiency. In hybrid vehicles, the brake torque demand is met by both the conventional friction braking system and an electric Regenerative Braking System (RBS). Hence, an effective ABS controller is required to achieve high braking efficiency without losing energy recuperation efficiency. This paper presents an Intelligent Sliding Mode Scheme (ISMS) to retain high energy recuperation efficiency as well as good braking efficiency of an EV with a unique braking configuration. The ISMS has a supervisory logic based motor torque limiter and slip controller. The slip controller is designed based on a two-wheeled model which has a hydraulic unit at the front producing frictional braking cooperating with a regenerative braking system with a brake-by-wire unit at the rear wheels. The slip controller is designed considering the hydraulics and motor actuator dynamics and the complete Magic Formula (MF) is used for tyre force estimation. The logic-based torque limiter not only regulates the brake torque to follow an assigned brake force distribution but also ensures that the battery is not overcharged

Passenger car active braking system: Pressure control design and experimental results (part II)

This paper deals with the design of a brake caliper pressure controller for a conventional anti-lock braking system/electronic stability control system and the experimental validation of its tracking performances. The analysis of the hydraulic plant, carried out in part I of this two-part study, is here utilized to develop the control algorithm. The control strategy is based on a feed-forward and a proportional integral controller through pulse width modulation with a constant frequency and variable duty cycle. The feed-forward contribution requires modeling of the nonlinear openloop system behavior which has been experimentally identified and described through two-dimensional maps: the inputs are the duty cycle applied to the electrovalves and the pressure drop across their orifice, while the output is the pressure gradient in the brake caliper. These maps, obtained for inlet and outlet valves, are used to set the feed-forward term. Finally a proportional integral controller is designed to reject external disturbances and compensate for model uncertainties. A brake system test rig, described in part I, is used for building inverse maps and validating the proposed control logic. Different reference pressure profiles are used to experimentally verify the control tracking performances

Intelligent traction motor control techniques for hybrid and electric vehicles

This thesis presents the research undertaken by the author within the field of intelligent traction motor control for Hybrid Electric Vehicle (HEV) and Electric Vehicle (EV) applications. A robust Fuzzy Logic (FL) based traction motor field-orientated control scheme is developed which can control multiple motor topologies and HEV/EV powertrain architectures without the need for re-tuning. This control scheme can aid in the development of an HEV/EV and for continuous control of the traction motor/s in the final production vehicle. An overcurrent-tolerant traction motor sizing strategy is developed to gauge if a prospective motor’s torque and thermal characteristics can fulfil a vehicle’s target dynamic and electrical objectives during the early development stages of an HEV/EV. An industrial case study is presented. An on-line reduced switching multilevel inverter control scheme is investigated which increases the inverter’s efficiency while maintaining acceptable levels of output waveform harmonic distortion. A FL based vehicle stability control system is developed that improves the controllability and stability of an HEV/EV during an emergency braking manoeuvre. This system requires minimal vehicle parameters to be used within the control system, is insensitive to variable vehicle parameters and can be tuned to meet a vehicle’s target dynamic objectives

New trends in electrical vehicle powertrains

The electric vehicle and plug-in hybrid electric vehicle play a fundamental role in the forthcoming new paradigms of mobility and energy models. The electrification of the transport sector would lead to advantages in terms of energy efficiency and reduction of greenhouse gas emissions, but would also be a great opportunity for the introduction of renewable sources in the electricity sector. The chapters in this book show a diversity of current and new developments in the electrification of the transport sector seen from the electric vehicle point of view: first, the related technologies with design, control and supervision, second, the powertrain electric motor efficiency and reliability and, third, the deployment issues regarding renewable sources integration and charging facilities. This is precisely the purpose of this book, that is, to contribute to the literature about current research and development activities related to new trends in electric vehicle power trains.Peer ReviewedPostprint (author's final draft