Parameter Dependencies: Problems and Solutions

Parameter Dependencies Problems and SolutionsAbstractThis masters thesis concerns breeding of embedded chequer establishments. Development make for for embedded operate systems involves several flavors, such as control design, rapid prototyping, fixed-point implementation and hardw be-in-the-loop-simulations.Another pervert, which Volvo is not currently using within climate control is on-line tuning. oneness reason for not using this technique today is that the avail subject roosters for this task (ATI Vision, INCA from ETAS or CalDesk from dSPACE) do not handle contention attendencies in a satisfactory way. With these constraints of today, it is not possible to use online tuning and controller development routine is more laborious and time eat.The main task of this thesis is to solve the line of work with disputation dependencies and to make online tuning possible.1 INTRODUCTION1.1 BackgroundVolvo technology (VTEC) is an innovation comp each that provides expert func tions and develops sweet technology for hard as intumesce as soft products within the transport and vehicle industry. Among other things VTEC is working with embedded control systems. For one of the embedded control systems particularly Climate work Module (CCM), VTEC is working with the whole chain. VTEC does this for Volvo Cars, Volvo Trucks, Volvo Construction Equipment, Renault Trucks and Land Rover.The work process for embedded control system developmet is typic totallyy as followsControl Designspeedy Control PrototypingFixed-Point ImplementationHardwar-In-the-Loop SimulationOnline Tuning.It is an iterative process, but on that point is one difficulty for the last meter, which limits the possibilities of working iteratively. Control design is typically make in MATLAB/Simulink and Fixed-Point implementation is typically made with a tool such as TargetLink. During these steps the parameters may be handled in an m- read. When going to the on-line tuning step however, the pa rameters atomic number 18 handled in a tool such as ATI Vision, INCA or CalDesk. Once you clear taken this step the connection to the m-file is lost. Therefore the last step is somewhat of a one-way step. It is not completely impossible to go back to the earlier steps in the development chain, but the iterative process is not well binded by available on-line tuning tools of today.The pursuance m-script instructions atomic number 18 examples of parameter dependencies that will cause the mentioned problemsHeating = - coulomb, -20, 0, 20, 100 BlowerHt = 12, 5, 4, 5, 10 Blower_min = min BlowerHtDefrosting = 0, 20, 100 BlowerDef = Blower_min, Blower_min, 10 Using the above vectors in interpolation tables, one table with Heating as input vector and BlowerHt as end product vector and another table with Defrosting as input vector and BlowerDef as output vector would cause problems during on-line tuning process. Three of the elements are meant to urinate identical set, but the to ols, as it is today would allow them to be tuned individually. This is just one of many constructs, which may be very useful as immense as you are in the MATLAB environment but causes problems during the on-line tuning process.1.2 Goals and objectivesThe main goals of this masters thesis areTo investigate the problem of parameter dependencies.To go steady possible solvings.To make online tuning possible for settlement parameters in the development process of embedded control systems..2 BACKGROUND2.1 EMBEDDED SYSTEMS2.1.1 History of implant SystemsIn the era of earliest development of computers i.e. 1930-40s, generally computers were capable of doing a single task. Over time with the advancement in technology, traditional electromechanical sequencers presented the supposition of programmable controllers using solid state devices.One of the first recognizably modern embedded systems was the Apollo Guidance Computer, developed by Charles Stark Draper at the MIT Instrumentation L aboratory.1 aft(prenominal)wards the early industriousnesss in 1960, the prices of embedded systems have come down and their processing power has been increased dramatically. A standard for programmable microcontrollers was released in 1978 by National plan Manufacturing Association. This standard was for almost any computer- homed controllers for example event-based controllers and single board computers.When the production cost of microprocessors and microcontrollers fell, it became feasible to replace old, big and expensive components like potentiometers and varicaps with microprocessor read knobs.With the consolidation of microcontrollers, the action of embedded systems has boost increased. The embedded systems are being utilize into areas where generally computers would not have been considered. Most of the complexity is contained within the microcontroller itself and very some additional components are needed. So because of this most struggle is in software area.(last sentence is difficult to understand).2.1.2 Common Characteristics engraft Systems have several common characteristics.Uni-Functional Embedded systems are usually designed to execute besides one program but repeatedly. For example, an ordinary scientific calculator will always do only calculations. While on the other hand, a laptop computer give the sack execute an enormous number of various programs, like web browsers, word processors, computer programing tools and video games. New programs or softwares are added very frequently.Tightly constrained All computing systems have constraints on design metrics, but these constraints undersurface be very tight for embedded systems. A design metric is defined as, a measure of an implementations features, such as cost, size, performance, and power. Embedded systems are ofttimes desired to cost just a few dollars, they mustiness be designed for minimum size to fit on a single chip, they must be able to perform fast processing in ball club to process real-time data, and they must consume minimum power in assemble to extend battery life or may be to prevent the need of a cooling fan.Reactive and real-time Many embedded systems should be able to continually react to smorgasbords in the systems environment. They must also compute received results in real time without too much delay. For example, a cruise controller in cars have to monitor and react to speed and brake sensors continuously. It must compute acceleration or decelerations repeatedly within quite contain time a delay in computation of results could result in a fatal failure to maintain control of the car. On the other hand, a desktop computer generally counsellinges on computations with comparatively infrequent reactions to input devices. In addition, a delay in those computations may perhaps be inconvenient to the user but that does not result in a system failure.2.2 pretence Based Design vex-Based design in short MBD is a mathematical and visual method of addressing problems associated with designing complex control systems. It is used in many industrial equipment designing, automotive and aerospace applications. Here in this thesis our focus is on climate control of new vehicles. This methodological analysis is used in designing embedded software.Embedded software development consists of four steps clay sculpture a plant.Analyzing and synthesizing a controller for the plant.Simulating the plant and controller.Integrating all these phases by developing the controller.Model-based design is quite different from the conventional designing method. In this methodology graphic designer use continuous and discrete time building blocks instead of using long and complex software coding.This model based design enables designer to fast prototyping, streaking and verification. Along with all these advantages, dynamic effects on the system can also be tested in hardware-in-the-loop (HIL) simulation mode. most important steps in model -based design approach areBy choosing appropriate algorithmic rule and acquisition of real-world system data, various types of simulations and analysis can be performed before producing a real controller.The model produced in step one is used to identify characteristics of the plant model. Then a controller can be made based on these characteristics.Using this model, the effect of time varying inputs can be analyzed. In this way the possible errors can be eliminated and it is very convenient to change and test any other parameters.Last step is deployment.Advantages of model based design compared with the conventional approach are as followsModel based design provides common design environment which is important for development groups from the view point of general communication and specifically for data analysis and system verification.Model based design enable sends to detect and correct errors in early phase of development. This is crucial point for minimizing time and financial impact of system.Model based design can be reused later for upgrading and for derivative systems which are capable to expand.2.3 ECU DEVELOPMENT2.3.1 Conventional Approach for ECU DevelopmentThe conventional approach for electronic control unit, ECU, development is summarized in following four stepsSome experienced personal define the functions and system architecture and then the hardware engineer design the hardware circuit.Control engineer design the control algorithms and a programmer generate a handwritten law for that algorithms.Then these control algorithm program codes and hardware are integrated and tested by system engineer or maybe hardware engineer.Then on the engine test bench the complete system is tested.There are few problems with this conventional approach for ECU development.First and very major problem is that the hardware circuits are made before the confirmation of control rules and results. Only this factor adds a big risk in the process of ECU development.Se condly if some error is encountered during the program code testing, it is very difficult to judge whether the error is because of software codes or in the control algorithms. This programming of the control algorithm is itself a very time consuming process and it take additional time when some errors are encountered and the process of debugging. Since many people from different field of work are involved in this process so coordination between them also take time and it makes the development cost to increase. 2Thats why the conventional development process can not reciprocate the demand of modern age and its requirements.2.3.2 Modern ECU DevelopmentOn the bases of integrated development environment, the modern development of electronic control units can be efficiently completed and tested. Using model based simulation and hardware-in-the-loop simulation it is very easy and convenient to eliminate software errors and to modify the control algorithms. Due to this the development co st is reduced and development efficiency is improved. This modern development process is called V-cycle development process.This process is illustrated in Ffig. 1. (when you use figures from other publications, you have to get liberty from the auther. It is not enough to put a reference)Fig. 1. The V-Cycle of model-based software development. 2This process is summarized as followsUsing very sophisticated tools like MATLAB/Simulink/Stateflow and dSPACE TargetLink, the control algorithms are modeled. These control algorithms are confirmed using off-line simulations.The ANSI C code is produced using code generation tool. The one we are using is dSPACE TargetLink.The code produced in above step is compiled and downloaded into the control module and simulation is done in Hardware-in-the-loop mode, which confirms the credibility of the control algorithms.This tested program code of control algorithms is downloaded into the electronic control unit for further test and modification.Finally normalization of the whole control system is done.2.4 Universal measurement and Calibration Protocol (XCP)XCP is a standardized and universally applicable protocol with much rationalization potential. It is not only used in ECU development, standardisation and programming, it is also used to integrate any desired measurement equipment for prototype development, operative development with bypassing and at SIL(define) and HIL(define) test stands.16For normalisation and measurements, it is common practice to connect electronic control units in a *CAN* ne cardinalrk. For this purpose CAN calibration protocol is used extensively. With increasing demands of more sophisticated controllers, new electronic control units are becoming more and more complex and for that reason new ne devilrks are being developed such as, FlexRay, TTCAN etc.(give references)To meet the needs of new ne cardinalrks, the measurement and calibration protocol should be more generalized and compromising. This gene ralized and flexible protocol is XCP (Universal measurement and calibration protocol).XCP is autarkic of transport layers. So in XCP, X generalizes the various transport layers that* Details rough CAN are provided in Appendix A.are used by the members of the protocol family e.g. 9XCP on CANXCP on FlexRayXCP on EthernetXCP on USB and so on(you have to refere to each figure)Fig. 2. XCP support for different transport layers 10.3 PROBLEM INVESTIGATIONThis chapter will give answers to the following questionsWhat is parameter addiction problem?What is the effect of parameter dependency problem on tuning of embedded control systems?What are the difficulties to solve the problem at different platforms?Note All examples used in this report are only for illustration purposes and are NOT the actual parameters used in climate control module of Volvo Cars and Volvo Trucks.3.1 Complete process for developing embedded control systemsThe complete process for developing embedded control systems is illustrated in Ffig. 3. First step of this development process is to define parameters and that can be done in the m-file. These parameter value are loaded into MATLAB base workspace from where TargetLink/Simulink model fetches these values to simulate the process.After checking the simulation results and doing some modifications if required, C-code is generated by TargetLink. That C-code contains all the info about the control algorithm and input values. In the next step the auto-generated C-code is compiled using a Green Hills Suite.Fig. 3. Complete Production(rapid prototyping process?) Process.Green Hills software together with gnu Make and VBF converter is used to generate a map file and VBF file (Volvo Binary Format). This vbf file is downloaded in the embedded controller. The map file is used to generate A2L file using TargetLink. This A2L file is required by the calibration tool (for this spew ATI romance is used for calibration) and then using this calibration tool w e can do parameters modifications in ECU. These modifications are also called tuning.3.2 Parameter settlementAs all parameters are defined in a m-file, some parameters depend on the values of some other parameters. It may also be possible that the values obtained as a result of calculation between two or more parameters are used in the definition of other parameters. So, all those parameters which contain some other parameters or calculations of some other parameters in their definitions are called dependent parameters e.g.In above example parametersParameter 2 is dependent on parameter 1.Parameter 4 is dependent on parameter 2 and 3.Parameter 6 is dependent on parameter 2 and 3.3.3 Reasons for introducing parameter dependenciesThinking of parameter dependencies a question may arise in minds that, Why do we need to introduce parameter dependencies at the first place?Answer to this question is that, when designing a control algorithm in a tool such as Simulink, it is convenient to u se named parameters (variables) instead of hard coded numbers (constants).For instance, if the highest fan available corresponds to a voltage of 13.5V. Designer may want to have a parameter for this, so that instead of using the value 13.5 at many instances of algorithm, the name of parameter stipulate for that value can be used. If one day that hardware is needed to be changed and for new hardware 13.4V is the maximum that can be used for highest fan level, then it is easier to change one parameter value rather than changing many hard coded values at different instances.Sometimes it is good to have one parameter depending on another. For instance in a look-up table, there are several values in each vector and these values may depend on other parameters. It would be rather limiting if a vector or a matrix could only contains hard coded numbers.So, the use of dependent parameters helps keeping a good structure in the algorithm. It makes easier to work with the parameters.3.4 Statisti cs about parameter dependencyThere are quite significant numbers of parameters which are dependent on other parameters. For instance in Climate Control P3, total number of parameters is 1618 out of which 227 parameters are dependent on other parameters and 1391 parameters are independent. We call independent parameters as Base Parameters.Fig.4 Percent of Dependent parameters3.5 Parameter dependency problem in development processTo analyze the problem of parameter dependency, lets walk by the development process of embedded control systems and find out what exactly is the problem with parameter dependencies.As the process starts with parameter definitions in m-file, so the probe starts from m-file, see Fig. 5.. To visualize this process, an illustration with an example of parameter with dependencies in its definition is shown as followsFig.5. Example of parameter definition in m-file.After defining all parameters, the m-file is run in MATLAB. In this step all the values of dependen cy parameters are evaluated by MATLAB and are loaded into MATLAB base workspace. Precisely during this loading process the dependencies are replaced by their values and any information about the relation of a parameter with dependency parameter is lost.Fig.6. Dependency loss in MATLAB base workspace.As now the dependency information is lost, so this loss will propagate through all the further steps, for example in C-code generation, A2L file and in strategy(?) file.Following F fig 7. shows that the propagation of dependency information loss. So in C-code there is no information with the help of which we can trace dependency parameters.Fig.7 Propagation of dependency loss from MATLAB to C-code.3.6 Effect of parameter dependencies on development processThe problem caused by parameter dependencies comes to the sur memorial tablet during the calibration step.During calibration the values of parameters are tuned. When the information of parameter dependencies is lost, then we have to tun e each parameter value individually. This is shown in the Ffollowing fig 8.Fig.8. Effect of dependency loss on development process.So if a parameter is used, for instance, in the definitions of five different parameters, then we have to tune the value of that parameter at those five locations individually. If there is any calculation involved in any parameter definition, then we must do it manually and update the value. This process of changing values manually is very time consuming and error prone.There is another curtain raising that to avoid doing these calculations and tuning parameter values individually. We can change the parameter values in the original m-file, where we have all parameter definitions and repeat the complete process again. This is very laborious work and it also takes a lot of time, so this possibility is not so feasible.4 POSSIBLE SOLUTIONSAs the complete process for developing embedded controllers is a multistage process and it depends on four exceedingly sophisticated software platforms. So there can be different approaches to solve the dependency information loss. Following are the possible platforms for doing modifications in order to handle the dependency loss problem.MATLABTargetLink modelC-codeCalibration toolSeparate windows applicationFollowing is the in depth analysis of above mentioned platforms and possibility of decision a feasible solution.4.1 Parameter dependencies and MATLABWhen m-script, containing all parameter definitions, is run in MATLAB, all parameter values are evaluated and stored in MATLAB base workspace. Right at this first step dependency information in m-script is lost. The Rreason of this loss is that MATLAB base workspace support values belonging to only one class type. That can be char, double, struct or any other class but the values can not belong to a mixture of two or more class types, i.e., values cannot consist of two elements of an array belonging to char class and other elements of array belongi ng to double class.(I guess that a struct can consist of chars as well of doubles)Fig.9. Supported Class types in MATLAB base workspace.In our case of parameter dependency for example, we have an array of 8th elements. Second element and eighth element of our example array are names of some other parameters, so these names belongs to char class and rilievo of elements of that array are numerical values belonging to double class. So MATLAB evaluates the values of dependency parameters and replace all names with their corresponding values and our dependency information is lost.Although there is a function in MATLAB called eval and this function can be used instead of dependency parameter name but this does not solve our problem because this function will evaluate the values of those parameters and eventually its the value of parameter which is updated in the base workspace and dependency information is still filtered out. lesson of the story is that we can not do anything in MATLAB to save our dependency information until unless MathWorks do some changes in MATLAB so that base workspace would be able to support values belonging to different classes in same definition. 4.2 Parameter dependencies and TargetLinkIn TargetLink we can use practise lookup tables and we can include custom code. Let us suppose for a moment that by adding these custom lookup tables and using some extra blocks we manage to introduce lost dependency information in TargetLink model. But when TargetLink will generate C-code, most probably it will evaluate all those values and resulting values will be include in C-code.There are two reasons for this behavior of TargetLinkFirst reason is that, TargetLink work inside MATLAB so all the calculations are done in MATLAB and we face the same problem as described previously.Second reason is that, dSPACE claims that TargetLink generates C-code in the most efficient way, because this C-code is flashed into controller in binary format, so it is the ma ximum effort of TargetLink to keep C-code as small as possible because of the limited memory of ECU and demand of high operational speed.So TargetLink does not generate extra variables and pointer in C-code until unless some significant changes are done in TargetLink by dSPACE.4.3 Parameter dependencies and C-codeC-code generated by TargetLink can be modified and it is possible to add any kind of extra information but there are two reasons which make this possibility impracticable.First reason is that, this C-code will be flashed into ECU and there is very limited memory in the control unit and bigger C-code will result into a less efficient embedded controller.Second reason which makes this possibility impracticable is that. iIt requires a lot of manual labor every time we change something. This is also error prone.4.4 Parameter dependencies and Calibration toolIn calibration tool like ATI VISION, there is an option to use script written in Vision scripting language or in Visual b asic. Instead of doing manual calibration we can automate calibration using the script.In our case, we have matrices with dependencies. So in order to do calibration using thescripting option we have to write function for doing matrix calculations and then that script must be able to evaluate dependencies tally to new values. So this option is not so feasible.4.5 Separate windows applicationAfter analyzing all possibilities only one option is left. That is to develop a separate windows application which will extract dependency information from m-script, calculate the values of dependency parameters according to the values tuned in calibration tool and will implement those new values of dependencies back in calibration tool.5 SELECTED SOLUTIONAfter analysis of all possible solutions, it is deducted that the most feasible solution to the dependency loss problem is a separate windows application whichExtracts dependency information from m-file.Gets tuned parameter values from calibrat ion tool.Calculates all values corresponding to those tuned parameter values.And implements updated values of dependency parameters back in calibration tool.5.1 Reasons for selecting this solutionAmong other solutions we have selected development of separate windows application, as a feasible solution. Major reasons for selecting this solution are as followsSelected solution which is developing a separate windows application does not need any modification of present softwares. This solution is fast, no extra licenses are required for this and it works just according to our requirements.If we choose any solution which includes modification in software tools, then that involves the involvement of tool makers. That process of convincing toolmakers to modify their software according to our requirements and if they declare then the process of developing and releasing new version of software may take very long time.Tool makers would charge a bully sum of money to make specified changes or for making an add-on application for the softwares.5.2 Overview of solutionThe solution is an application named Dependency Calibrator. It works in two steps.In the first step the m-file is parsed and the information of dependency parameter along with their location in parent parameter areis extracted and rearranged in a way that it can be used in the second step that is calibration.During the second part of the process, first of all the application will import data from VISION so that if user has tuned any value in calibration tool, that data will be updated in MATLAB and then the application will do calculations in MATLAB after that new values obtained as a result of those calculation will be updated again back to VISION. This cyclic process from VISION to MATLAB and back to VISION will update parameter values. If user has changed values which was used by other parameters, those new values will be updated on all locations where they are used. This is shown in the following figFi g. 10..Fig. 10. Overview of solution.The application Dependency Calibrator is divided into two parts.ParserCalibratorDetailed explanation of how this application isn working is as follows.5.3 Required SoftwaresParser works without any requirement of external software but in order to run Calibrator following softwares must be installed on your systemMATLAB R2007bATI VISION 3.5.3MATLAB is automatically launched by the application but make sure to launch ATI VISION before you use Calibrator part of Dependency Calibrator application.5.4 Project fileProject file is a call to control the Dependency Calibrator application. Instead of using hard coded paths for different files used in this application, an option is given to the users to select their desired locations. These locations can be specified in a separate file which is named as project file.In this project file the instructions can be given after certain tags. One must be very careful because these tags should not be altered. Whil e user inputs can be given after the symbol .Dependency Calibrator application is in fact capable of handling multiple m-files and multiple c-files. Directory path for these files can be specifies in project file.Project file contains following tagsVISIONs spin Name After this tag, name of the hardware device which is used in the VISION device tree, should be given. For example, VISIONs Device Name PCM Or VISIONs Device Name CCMPath of m buck After this tag the full path for m-file should be given. If number of m-files is more than one, then this tag followed by file path of those m-files should be given on a new line. Parser will read all these files and will merge them into one file. For example, Path of m File CFolderNamesubFolderFile_Name.m Path of m File CFolderName2subFolder2File_Name2.m radix directory for c files In general practice c files can be generated in different folders but their subside directory remains same. So in order to avoid repeating same addres s and to minimize the chances of error this tag is introduced in project file. So after this tag path of root directory for c files should be specified. Please note that there should be no at the end of root directory path. For example Root directory for c files DABC_XYZsubFoldersubSubFolders containing c-files After this tag the names of folders which contain c files should be specified. If there are more than one folder containing c files then those folders names should be added after a comma ,. The parser will then search these folders for all c files contained in them. For example Folders containing c-files FolderMedCfiles,subFoldercFolderRoot Output Directory This tag should be followed by the path for required location where the user wants the application to generate all files. For example Root Output Directory CExtra File for calibrating non-calibratable parameters After this tag, there should be the path for the file containing names of those parameters which are not calibratable but they are desired to be set in VISION. Those names should be exactly the same as defined in m-file, followed by underscore _ and followed by any desired word or character.For example Extra File for calibrating non-calibratable parameters CExtraParNames.txt5.5 ParserThe F first part of the complete dependency calibration process is the parser. When Parser is executed, a window appears showing two options, Load Project Fil