With the rapid growth in the automotive industry, vehicles have become more complex and sophisticated. Vehicle development today, involves integration of both electrical and mechanical systems. Their design and production are typically time and cost critical. To complement and support the process of vehicle development and design, majority of the automotive industry use modelling and simulationfor testing automotive applications, vehicle subsystems or the vehicle behaviour in its entirety. For the purpose of traffic simulations, where a large number of vehicles and other elements of the road network are simulated, implementing a highly complex vehicle model would greatly affect the performance of the simulation. The complexity of the vehicle model would entail a higher computation time of the system, making it unsuitable for any real time application. There in lies the trade-off indesigning a model that is both fast and accurate. The majority of the vehicle models that have been designed are either domain specific, highly complex or generalized. Thus, in this thesis, two class specific vehicles’ kinematic models with good accuracy and low computation time are presented. Two different modelling paradigms have been adopted to design and test these models. The results, challenges and limitations that pertain to these paradigms are also presented and discussed. The results show the feasibility of the proposed kinematic models.

This thesis explores the conceptual design process of complex hydromechanical transmissions for mobile working machines. Efficient methods for design optimisation and controller development are presented to support the final concept selection. In the endeavour to develop new fuel-efficient driveline solutions for construction machines and off-road equipment new complex hydromechanical transmission concepts are being investigated. This pursuit is driven by stricter emission legislation, high fuel prices and a desire for a greener image both for customers and manufacturers. The trend towards more complex transmission architectures increases the need for more sophisticated product development methods. Complex multiple-mode transmissions are difficult to design and prototype and can be realised in a great number of architectures. By introducing a secondary energy storage in the machine the design space expands further for both hardware and software. There is accordingly a need for more reliable concept assessment in early design stages and the possibility to support concurrent engineering throughout the development process. Previous research on the design and development of hydromechanical transmissions has been limited to analysis of fixed concept designs or design optimization using very simple performance indicators. Existing methodologies for electrified on-road vehicles are not suitable for off-road working machines with hydromechanical transmissions and hydraulic energy storage. The proposed conceptual design process uses detailed quasi-static simulation models and targets to optimise the fuel efficiency of the specific machine specifications and operations. It is also shown how high-speed dynamic simulations can be used for controller development and hardware-in-the-loop simulations to support an efficient product design process. The methods are demonstrated for typical use cases targeting new transmission development for construction machines. Software control development is also treated using control optimisation and real-time simulation. Finally a novel hybrid hydromechanical motion system is presented for which an efficient design process is crucial to its end performance. / <p>In the printed verison the series name <em>Linköping studies in Arts and Science</em> is incorrect. The correct series name is <em>Linköping studies in science and technology. Dissertations</em>.</p>

Handling the software complexity of modern vehicle functionalities has become very challenging due to their non-centralized nature and real-time requirements that they impose.  These functionalities are usually developed as distributed real-time embedded systems composed of several nodes (Electronic Control Unit) and multiple communication protocols. Among many software development paradigms for these systems, the model-based approach excels mainly for two reasons. First, it handles the software complexity by separation of concerns through the use of models. Second, it ensures the timing predictability of these systems by adopting the timing analysis techniques proposed by the research community. They are pre-runtime timing analysis techniques that provide shreds of evidence whether all the timing requirements will be met during the execution of the system. In this thesis work, we propose a comprehensive framework that captures the timing related information needed for the modeling languages to facilitate these timing analyses. The framework is comprehensive in such a way that it identifies the generic timing properties for the nodes and network respectively. What is more, the system's timing model generated by the modeling languages requires tool support for extracting and interpreting this information. Hence, we validate the applicability of the framework by comparing two modeling languages and their respective tool-chains such as Rubus-ICE and APP4MC used in the vehicular industry.

Designing modern aircraft is not an easy task. Today, it is not enough to optimize aircraft sub-systems at a sub-system level. Instead, a holistic approach is taken whereby the constituent sub-systems need to be designed for the best joint performance. The State-of-the-Art (SotA) in simulating and exchanging simulation models is moving forward at a fast pace. As such, the feasible use of simulation models has increased and additional benefits can be exploited, such as analysing coupled sub-systems in simulators. Furthermore, if aircraft sub-system simulation models are to be utilized to their fullest extent, opensource tooling and the use of open standards, interoperability between domain specific modeling tools, alongside robust and automated processes for model Verification and Validation (V&amp;V) are required. The financial and safety related risks associated with aircraft development and operation require well founded design and operational decisions. If those decisions are to be founded upon information provided by models and simulators, then the credibility of that information needs to be assessed and communicated. Today, the large number of sensors available in modern aircraft enable model validation and credibility assessment on a different scale than what has been possible up to this point. This thesis aims to identify and address challenges to allow for automated, independent, and objective methods of integrating sub-system models into simulators while assessing and conveying the constituent models aggregated credibility. The results of the work include a proposed method for presenting the individual models’ aggregated credibility in a simulator. As the communicated credibility of simulators here relies on the credibility of each included model, the assembly procedure itself cannot introduce unknown discrepancies with respect to the System of Interest (SoI). Available methods for the accurate simulation of coupled models are therefore exploited and tailored to the applications of aircraft development under consideration. Finally, a framework for automated model validation is outlined, supporting on-line simulator credibility assessment according to the presented proposed method. / <p>Ytterligare forskningsfinansiär: Saab Aeronautics</p> / Model Validation – from Concept to Product / Open Cyber-Physical System Model-Driven Certified Development (OpenCPS).

Although automated greenhouse systems are widely used in industrial horticulture, the availability of similar, but simpler and affordable systems for residential greenhouses is low. The purpose of this project is, therefore, to design and develop a smart greenhouse system that supports standalone and remote monitoring and control of residential greenhouses. More specifically, this thesis focused on the design and implementation of the user interface and communication model of a smart greenhouse system. This project proposes a system architecture that can be used for converting a regular greenhouse into a smart greenhouse. The purpose of this is to enable users to monitor and control vital crop factors based on their needs. The resulting system is a userfriendly mobile application, a cloud-based storage service, and a responsive greenhouse system. Further development could focus on user experience and publish/subscribe distribution to achieve low power consumption. / Automatiska växthussystem används i stor utsträckning inom industriell trädgårdsodling men tillgängligheten för liknande, enklare och prisvärda system för bostadshus är låg. Syftet med detta projekt är därför att designa och utveckla ett smart växthussystem som stödjer monitorering och kontroll av mindre privata växthus. Denna avhandling fokuserar specifikt på design och implementering av ett användargränssnitt och en kommunikationsmodell för ett smart växthussystem. Detta projekt föreslår en systemarkitektur som kan användas för att konvertera ett vanligt växthus till ett smart växthus. Syftet med detta är att göra det möjligt för användare att övervaka och kontrollera viktiga grödofaktorer baserat på deras behov. Det resulterande systemet är en användarvänlig mobilapplikation, en molnbaserad lagringstjänst och ett responsivt växthussystem. En vidareutveckling av systemet kan fokusera på användarvänlighet och publish/subscribe distribution för att uppnå låg energiförbrukning.

The popularity of railway transportation has been on the rise over the past decades, as it has been able to provide safe, reliable, and highly available service. The main challenge within this domain is to reduce the costs of preventive maintenance and improve operational efficiency. To tackle these challenges, one needs to investigate and provide new approaches to enable quick and timely data collection, transfer, and storage aiming at easier and faster analysis whenever needed. In this thesis, we aim at enabling the monitoring and analysis of collected signal data from a train propulsion system. The main idea is to monitor and analyze collected signal data gathered during the regular operation of the propulsion control unit or data recorded during the regular train tests in the real-time simulator. To do so, we have implemented a solution to enable train signal data collection and its storage into a .txt and .CSV file to be further analyzed in the edge node and in the future connected to the cloud for further analysis purposes. In our analysis, we focus on identifying signal anomalies and predicting potential failures using MathWorks tools. Two machine learning techniques, unsupervised and supervised learning, are implemented. Additionally, in this thesis, we have investigated ways of how data can be efficiently managed. We have also reviewed existing edge computing solutions and anomaly detection approaches using a survey as a suitable method to identify relevant works within the state of the art. / RELIANCE

Increasingly different types of information are required in systems, resulting in the diverse and widespread use of networks. The increase in the number of devices on networks significantly increases network traffic and network load, limiting network propagation speed, and increasing the possibility of collisions and lost information. One way to identify the size of the network load is by measuring the network occupancy. Although speeds are constantly increasing, some parts of the network can still become the bottleneck. Therefore, it is always desirable to minimize network occupancy. In this paper, an approach for the multi-constrained network occupancy optimization is presented. The objective is to minimize network occupancy by optimizing the packing process. The problem is identified as a bin packing problem, which is strongly NP-hard. The modification of the Best-Fit Decreasing algorithm is implemented to find the best solution while satisfying multiple constraints. The approach considers grouping signals that are sent to different controllers in the same packages. The analysis is done on the medium-sized plant model, and different topologies were tested. The results show that the proposed solution gives less network occupancy compared to the reference case. Also, by changing the relative placement of network nodes, a significant reduction in network occupancy is achieved.

Embedded network software has become increasingly interesting for both researchand business as more and more networked embedded systems emerge.Well-known infrastructure protocol stacks are reimplemented on new emergingembedded hardware and software architectures. Also, newly designed orrevised protocols are implemented in response to new application requirements.However, implementing protocol stacks for embedded systems remains a timeconsumingand error-prone task due to the complexity and performance-criticalnature of network software. It is even more so when targeting resource constrainedembedded systems: implementations have to minimize energy consumption,memory usage and so on, while programming efficiency is needed toimprove on time-to-market, scalability, maintainability and product evolution.Therefore, it is worth researching on how to make protocol stack implementationsfor embedded systems both easier and more likely to be correct withinthe resource limits.In the work we present in this thesis, we take a language-based approachand aim to facilitate the implementation of protocol stacks while realizingperformance demands and keeping energy consumption and memory usagewithin the constraints imposed by embedded systems. Language technologyin the form of a type system, a runtime system and compiler transformationscan then be used to generate efficient implementations. We define a domainspecificembedded language (DSEL), Implementation of Protocol Stacks (IPS),for declaratively describing overlaid protocol stacks. In IPS, a high-level packetspecification is dually compiled into an internal data representation for protocollogic implementation, and packet processing methods which are thenintegrated into the dataflow framework of a protocol overlay specification.IPS then generates highly portable C code for various architectures from thissource. We present the compilation framework for generating packet processingand protocol logic code, and a preliminary evaluation of our compiled code. / IPS

The promising results of deep learning (deep neural network) models in many applications such as speech recognition and computer vision have aroused a need for their realization on embedded platforms. Augmenting DL (Deep Learning) in embedded platforms grants them the support to intelligent tasks in smart homes, mobile phones, and healthcare applications. Deep learning models rely on intensive operations between high precision values. In contrast, embedded platforms have restricted compute and energy budgets. Thus, it is challenging to realize deep learning models on embedded platforms. In this thesis, we define the objectives of implementing deep learning models on embedded platforms. The main objective is to achieve efficient implementations. The implementation should achieve high throughput, preserve low power consumption, and meet real-time requirements.The secondary objective is flexibility. It is not enough to propose an efficient hardware solution for one model. The proposed solution should be flexible to support changes in the model and the application constraints. Thus, the overarching goal of the thesis is to explore flexible methods for efficient realization of deep learning models on embedded platforms. Optimizations are applied to both the DL model and the embedded platform to increase implementation efficiency. To understand the impact of different optimizations, we chose recurrent neural networks (as a class of DL models) and compared its' implementations on embedded platforms. The comparison analyzes the optimizations applied and the corresponding performance to provide conclusions on the most fruitful and essential optimizations. We concluded that it is essential to apply an algorithmic optimization to the model to decrease it's compute and memory requirement, and it is essential to apply a memory-specific optimization to hide the overhead of memory access to achieve high efficiency. Furthermore, it has been revealed that many of the work understudy focus on implementation efficiency, and flexibility is less attempted. We have explored the design space of Convolutional neural networks (CNNs) on Epiphany manycore architecture. We adopted a pipeline implementation of CNN that relies on the on-chip memory solely to store the weights. Also, the proposed mapping supported both ALexNet and GoogleNet CNN models, varying precision for weights, and two memory sizes for Epiphany cores. We were able to achieve competitive performance with respect to emerging manycores. As a part of the work in progress, we have studied a DL-architecture co-design approach to increase the flexibility of hardware solutions. A flexible platform should support variations in the model and variations in optimizations. The optimization method should be automated to respond to the changes in the model and application constraints with minor effort. Besides, the mapping of the models on embedded platforms should be automated as well.

The requirements of safety-critical real-time embedded systems pose unique challenges on their design process which cannot be fulfilled with traditional development methods. To ensure their correct timing and functionality, it has been suggested to move the design process to a higher abstraction level, which opens the possibility to utilize automated correct-by-design development flows from a functional specification of the system down to the level of Multiprocessor Systems-on-Chip (MPSoCs). ForSyDe, an embedded system design methodology, presents a flow of this kind by basing system development on the theory of Models of Computation and side-effect-free processes, making it possible to separate the timing analysis of computation and communication of process networks. To be able to offer guarantees on the timing of tasks implemented on a MPSoc, the hardware platform needs to provide predictability and composability in every component, which in turn requires a range of special considerations in its design. This thesis presents a predictable and composable FPGA-based MPSoC template based on the Altera Nios II soft processor and Avalon Switch Fabric interconnection structure and its integration into the automated ForSyDe system design flow. To present the functionality and to test the validity of timing predictions, two sample applications have been developed and tested in the context of the design flow as well as on the implemented hardware platform.