ME Mechatronics systems in automobile Adaptive semi active

ME 1202: Introduction to Mechanical Engineering
Mini Project
Presented by
Gunarathne G.W.L.A.

24th June 2018
Department of Mechanical & Manufacturing Engineering
University of Ruhuna
List of figures
List of tables
Principles and technology
Information processing structure
Multilevel control for mechanical systems
Various related applications and extensions
Mechatronics systems in automobile
Adaptive semi active vehicle suspension system
Selftuning damping of diesel engine drive chain oscillations
Roll of mechanical engineer
Integration of mechanics, electronics, and information technology leads to mechatronic systems
Advanced intelligent automatic system with multi control levels, knowledge base, inference
Mechanism and interfaces
Knowledge based multilevel feedback control for mechatronic systems
Simplified model of the vertical dynamics (linear part)
Estimated damping coeffincient dA and coulomb friction FR my measurement of (ZR-ZA) on a quarter car test stand
Parameter-adaptive suspension system with state and parameter feedback
Body acceleration versus dynamic tire load variation
Feed forward and feedback control scheme for diesel engines
Splitting engine-vehicle dynamics into a low frequency and high frequency part and applying a band pass filter to obtain the drive chain oscillations
Drive chain oscillation without and with electronic damping for an acceleration experiment with the real Diesel-engine and a dynamometer
Steps in the design of mechatronic systems
Properties of conventional and mechatronic designed systems
Realization examples of mechatronic systems in cars for the properties given in Table 2
The integration of mechanical processes and microelectronics towards mechatronic systems opens new possibilities as well for the design of mechanical components as for automatic functions. The contribution discusses tirst the involved mechanical components and machines and the ways of integration. Then the different automation functions are described in the frame of intelligent control systems which contain multilevel control functions, a knowledge base, and inference mechanisms. Multilevel feedback control for mechanical systems comprises lower level and higher level control, including e.g. nonlinear adaptive control and fuzzy control. The inclusion of model based supervision and fault diagnosis is a further development step. Two examples of mechatronic systems for cars are shown, like an adaptive suspension system and self-tuning damping of drive chain oscillations
Mechanical systems are increasingly integrated with actuators, sensors and electronics. Besides the basic energy flow in the mechanical system an information flow in the electronic system enables a variety of automatic functions. This leads to mechatronic systems which consist of
mechanics (mechanical engineering, precision mechanics) and coupled processes (e.g. thermal, electrical)
electronics (microelectronics, power electronics, measurement and actuator technology)
information technology (systems theory, automation, communication, software-design, artificial intelligence)
see e.g. lEE (1990), Bradley et al (1991), McConaill et al (1991), Schweitzer (1992), Isermann (1993, 1996), Fig. 1. The design of the functions within mechatronic systems is performed as well on the mechanical as on the digital electronic side. Herewith the mutual interrelations play an important role and the creation of synergetic effects.

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Figure 1 : Integration of mechanics, electronics, and information technology leads to mechatronic systems
Mechatronic systems are developed for mechanical elements, machines and vehicles, and precision mechanics. Examples are:
1). mechanical elements with integrated electronics
Suspension systems
Vibration dampers
Clutches, elastic or with friction
Bearings, mechanical or magnetic
Gears, mechanical (tooth-, chain-, belt-gears)

2).machines with integrated electronics
Power producing machines like electrical drives, pneumatic and hydraulic drives water-, steam-, gas-turbines, combustions engines, etc.

Power consuming machines like generators, pumps, compressors, machine tools, robots, printing machines, etc.

Vehicles, like automobiles, ships, aircraft
3).precision mechanics with integrated electronics
telecommunication devices
consumer electronics
data processing devices
sensors and actuators
optical and medical devices

Table 1: Steps in the design of mechatronic systems
16764041783000The size of circle indicates the present intensity of the respective mechatronic development step:
464820046990002428875-508000 Large medium little
Precision mechanical Mechanical elements Machines
Pure mechanical system 69342037401505086352984500 69342037401505219702984500 59817038354004210052984500
1.addition of sensors, actuators, microelectronics, control functions
2.Integration of compoments (hardware integration)
3.Ingration by information processing(software integration)
4.redesign of mechanical system
5.creation of synergetic effects
499110191770006838952555240068389520408900069342010121900068389551689006838951469390050292022110700051244516967200051244511537950051244566802000 683895248856500598170229806500693420198374000693420150749000693420101219000683895516890005219701153795005219701649095005219701727200052197066929000 598170248856505981701955165059817014408150502920229806500598170926465051244512407900051244517456150051244573596500598170526415042100517272000
Fully integrated mechatronic systems
50863518288000 59817017462500 55054525082500
Examples: Sensors actuators disc- storages cameras Suspensions dampers chriches gears brakes El. Drives combustion engines machine, tools robots
Beginning with a classical mechanical-electrical systems which results from adding available sensors and actuators to the mechanical components one can mainly distinguish two
Table 2: Properties of conventional and mechatronic designed systems

Conventional design Mechatronic design
Added components Integration of components (hardware)
1 Bulky Compact
2 Complex mechanisms Simple mechanisms
3 Cable problems
Bus or wireless communication autonomous units
4 Cable problems Simple control Integration by information processing (software)
5 Stiff construction Elastic construction with electronic damping
6 Feed forward control linear (among) control Programmable feedback control(nonlinear) digital control
7 Precision through narrow lolearncesPrecision through measurement and feedback control
8 Nonmeasurable quantities change urbiteranlyControl of nonmeasurable estrimated quantites9 Simple monisoringSupervision with fault diagnosis learning abilities
10 Fixed abilities
Table 3: realization examples of mechatronic systems in cars for the properties given in
Table 2
Conventional design Mechatronic design
Added components Integration of components (hardware)
1 Mechanical duplex carbonator Electronic injection
2 Mechanical controlled injection pump with rotating piston High pressure pump and magnetic injection values
3 Many cables Bus cable
4 Belt driven maxiliariesDecentralized driven muxiliariesSimple control Integration by information processing (software)
5 Stiff drive chain Elastic drive chain with algorithmic damping through engine control
6 Mechanical gas pedal Electronic nonlinear throttle control
7 Feedforward controlled actuators Feedback controlled actuators with friction compensation
8 Manual steering of cars during spinning Feedback control of slip angle by state abserver and differential breaking
9 Monitoring of exhaust gases through maintemance inspection On board misfire derection by speed measurement of crankshaft
10 Fixed programs for automatic gear Adaptation of automatic gear to individual driver
Kinds of integration for mechatronic systems,
1. Integration of components (tegration in)
2.integration by information processing (software integration)
Table 1 shows five important development steps for mechatronic systems, starting from a purely mechanical system and resulting in a fully integrated mechatronic system. Depending on the kind of the mechanical system the intensity of the single development steps is different. For precision mechanical devices already fairly integrated mechatronic systems do exist. The influence of the electronics on mechanical elements may be considerable, as shown by adaptive dampers, anti-blocking system brakes and automatic gears. However, complete machines and vehicles show first a mechatronic design of their elements and then slowly a redesign of parts of the overall structure as can be observed in the development of machine tools, robots and vehicle bodies.
Table 2 indicates some properties of conventional and mechatronic systems and the advantages gained by the integration and Table 3 some examples for mechatronic systems for car.

The information processing within mechatronic systems may range between simple control functions and intelligent control, as shown in Fig. 2. An intelligent control system is organized as an on-line expert system and comprises multi control functions (executive functions) knowledge base inference mechanism communication interfaces The on-line control functions are usually organized in multi levels: • level I: level 2: level 3: level 4: low level control (feed forward, feedback) high level control (advanced control) supervision incl. fault diagnosis optimization, coordination level 5: process management The knowledge base contains quantitative and qualitative knowledge. The quantitative part operates with analytic (mathematical) process models, parameter and state estimation methods, analytic design methods (e.g. for control and fault detection), and quantitative optimization methods. Similar modules hold for the qualitative knowledge, e.g. in form of rules (fuzzy and soft computing). Further knowledge is the past history in the memory and the possibility to predict the behavior. Finally tasks or schedules must be known. The inference mechanism draws conclusions either by quantitative reasoning (e.g. Boolean methods) or by qualitative reasoning (e.g. possibilistic methods) and takes decisions for the executive functions. Finally communication between the different modules, an information management data base and the man-machine interaction has to be organized.
Based on these functions of an on-line expert system an intelligent system can be build up, with the ability “to model, reason and learn the process and its automatic functions within a given frame and to govern it towards a certain goal”. Hence, intelligent mechatronic systems can be developed, ranging from “low-degree intelligent”, Isermann (1996), as intelligent actuators, to “fairly intelligent systems”, as e.g. self navigating automatic guided vehicles.

Figure 2 : Advanced intelligent automatic system with multi control levels, knowledge base, inference mechanism and interfaces
Because of the integration of various functions the use of modern tools plays an important rule for the design of the control system if higher performances are required. It is proposed to consider the basic control as a knowledge based multilevel feedback control system which is shown in Fig 3. It is a part of the intelligent system of Fig. 2. The knowledge base consists of mathematical process models, parameter estimation and controller design methods and control performance criteria. The feedback control is organized in lower level and higher level controllers, a reference value generation module and controller parameter adaptation. With this structure the main control functions of mechatronic systems can be organized. The design of control systems for mechanical processes is characterized by e.g.:

Figure 3 : knowledge based multilevel feedback control for mechatronic systems
process model structure through theoretical modeling
unknown parameters determined by parameter estimation
adaptive compensation of nonlinear characteristics
friction compensation by dithering or parameter estimation
lower level control by PID or state controller
higher level control by PID, state controller or fuzzy-control
The integration of electronics into automotive systems plays an important role in the present development, see e.g. Kiencke(1995).This hole mainly for following parts:
components: actuators, sensors, microelectronics
engine management
drive chain automation
body/suspension control
braking system control
steering control
cruising control
In the sequel some results of own research are described and their relevance to mechatronic aspects are discussed.

Known adaptive and semi-active suspention control systems use fixed or scheduled controller parameters.Sharp et al (1987).Kraus et al (1970).Therefore some changes in vehicle conditions are not directly taken into consideration.Paramater adaptive suspension control systems were developed based on real-time parameter estimation which take into account changing vehicle conditions.The methods are based on a simplified model of the vertical dynamic behavior, figure 4.By measurement of e.g. the spring deflection (ZA-ZB) and the body acceleration ZA the damping coefficient dA the mass mA and the Coulomb friction FR can be estimated for given spring stiffness CA.

Figure 4 :Simplified model of the vertical dynamics (linear part)
Nonlinear, direction dependent continuous time models are used for parameter-estimation with discrete square root filtering (DSFI).Figure 5, figure 6 shows a semi-active parameter-adaptive system with a feedback of the signals (ZR-ZA) and adaptation of the continuously adjustable damping coefficient dA of the damper.By this adaptive shock absorber system an improvement of both, driving comfort and safety can be achieved, figure 7.

Figure 5 : Estimated damping coeffincient dA and couloumb friction FR my measurement of (ZR-ZA) on a quarter car teststand4.2 SELFTUNING DAMPING OF DLESEL-ENGINE DRIVE CHAIN OSCLILLATIONS
Modern realizations of digital control for Diesel-engines in cars use look-up tables for fuel mass and delivering time.

Figure 6 : Parameter-adaptive suspension system with state and parameter feedback

Figure 7 : Body acceleration versus dynamic tire load variation
The injection pump.Hence, mainly feedforward control is applied.Because of light and flexible construction of the drive chain and the strong torque oscillation of diesel-engines with manual shift low damped ascillations are a severe problem in the design of cars.These oscillations can now be damped by measuring the engine speed n and an electronic feedback to the feedforward controller, figure 8.The dynamics of the Diesel-engine and the driven vehicle can split into a low frequency part,figure9.The drive chain oscillation can in this case only be influenced in the range of 0.5 Hz<f<10 Hz.Therefore the engine speed is low pass and high pass filtered, resulting in a band pass filter, figure 9.The transfer behavior between the engine torque and the filtered speed signal can then be described by a second order transfer function with lead-lag behavior and different parameters for each gear.Applying recursive least squares estimation the parameters are identified on-line.The torque T is reconstructed with signals from the feedforward control.Based on the identified model the damping feedback with proportional-differential behavior is designed via numerical parameter optimization.Hence, a parameter adaptive feedback results which adjusts the controller parameters automatically for changing engine and vehicle behavior and selected gear shift.

Figure 8 : Feedforward and feedback control scheme for diesel engines

Figure 9 : Splitting engine-vehicle dynamics into a low frequency and high frequency part and applying a band pass filter to obtain the drive chain oscillations
The selftuning system was realized with a real diesel-engine and a dynamic engine dynamometer where the vehicle including drive chain is simulated by a high frequency controlled d.c.motor, figure 10.The digital control is performed by a VME-bus computer and a sampling time of T=10ms.The diesel-engine is a 1.61 VW-Golf with 40kW.

Figure 10 shows the speed oscillations without and with self-tuning digtal electronic damping.The first half oscillation is reduced by 20%, the second half oscillation almost completely.Instead of oscillations of about 1s duration the electronic feedback allows a strong damping within 0.4s.

Figure 10 : Drive chain oscillation without and with electronic damping for an acceleration experiment with the real Diesel-engine and a dynamometer
The systematic integration of mechanical systems and micro-electronics plays a crucial role in the further development of mechanical elements, machines, vehicles and precision mechanics towards mechatronic systems.The integration can be performed by two kinds, through the integration of components and through the integration by information processing.Information processing structures for mechatronics systems are characterized by multi-level control functions(from low level control through supervision to overall process management), making intensive use of model based and adaptive approaches.Advanced control methods for mechanical systems include enonlinear process models, parameter and state estimation, friction compensation and higher level feedforward or feedback in form of adaptive control and fuzzy control.

Another feature of mechatronic systems is the possibility for an automatic supervision with fault detection.Process model based methods allow the generation of analytical symptoms and even a fault diagnosis by reasoning methods.This is a prerequisite to improve the reliability and safety, to reduce maintenance costs and to trigger redundancy and reconfiguration.The design of mechatronic systems should be supported by CAD software tools for modeling, simulation and control design.A special role plays the hardware in the loop simulation for botsh the mechanical and the electronic parts.Application examples for cars have shown some features of mechatronic systems generated by advanced information processing.

Mechatronic systems will become more and more intelligent, making use of quantitative and qualitative process knowledge bases and inference mechanisms in the higher automation levels.

Mr.Appuu kuttan K.K – Introduction to Mechatronics
Mr.W.Bolton – Mechatronics Electronic Control Systems in Mechanical and Electrical Engineering
Mr.Clarence W.De Silva- Mechatronic systems (Devices , Design , Control , Operation and Monitoring)


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