Search Results (27)

Recent years have seen increasing attention paid to autonomous decentralized microgrids that are disaster-resistant and suitable for local consumption of locally generated renewable energy power. Although various methods have been discussed for achieving microgrids through autonomous decentralized cooperative control, there are few reports that have reached the stage of field testing. In this study, I propose a novel method for configuring the baseline of DC microgrids, where storage batteries are distributed and directly connected to the DC bus. I have built a testbed to demonstrate the operation of the DC microgrid through autonomous decentralized cooperative control. My method simply employs the droop characteristics inherent in batteries, and I introduce the new concept of a ‘weakly coupled grid’. This approach allows the realization of microgrids with autonomous decentralized cooperative control without the need for advanced and complex grid control technologies using DC/DC converters, and with a simple configuration. Additionally, by directly connecting batteries to the baseline, I introduce a grid stabilization method achieved by imparting electrical inertia to the baseline. This paper describes the construction method, the operation principle, and safe and stable operational methods for autonomous decentralized microgrids using this approach, aiming to serve as a guide for those who wish to build autonomous decentralized controlled microgrids in practice. Full article

Modern mobility faces increasing challenges, like carbon-free transportation and the need for flexible transportation solutions. The U-Shift II project addresses these problems through a modular electric vehicle architecture, a drive unit (Driveboard) and a vehicle body (Capsule). This separation offers high flexibility in different use cases. Current architecture paradigms, like AUTOSAR, face limitations in cost and development speed. To address these issues, this paper introduces a hybrid software architecture that integrates signal-oriented architecture (e.g., CAN bus) with service-oriented architecture for enhanced flexibility. A integral component of the hybrid architecture is the dynamic link system, which bridges these architectures by dynamically integrating Capsule-specific components into the Driveboard software stack during runtime. The performance of the developed systen and its functionality were evaluated using a hardware setup integrated into a Driveboard prototype. The dynamic link aystem was evaluated including latency measurements, as well as functionality tests. Additionally, a cloud-based reconfiguration process enhances the versatility of the Driveboard by allowing for over-the-air software updates and resource allocation. The results show a promising hybrid, reconfigurable E/E architecture that aims to enable a robust transition towards a pure service-oriented architecture required in future electric autonomous vehicles. Full article

The integrity of the $12\mathrm{V}\mathrm{dc}$ power distribution system on a vehicle is essential to guarantee continuous power supply to safety-relevant consumers. Safety-relevant consumers are critical loads, for example, electric power steering, braking systems with functionalities like Anti-Lock Braking or Electronic Stability Control, and autonomous drive systems. To prevent insufficient power supply for safety-relevant consumers due to an increased wiring harness resistance, a novel diagnostic approach is developed to determine the condition of the power distribution, especially the electrical resistance. The influence of measurement errors and bus commutation on the estimation is investigated by using a simulation. By using the diagnostic, a resistance determination in the milliohm range with a standard deviation of $\sigma =0.3\mathrm{m}\Omega$ can be achieved under realistic conditions. This ensures that failures in the wiring harness can be identified, avoiding cascading effects and minimizing recalls. Compared to the state of the art, redundancies, costs, and weight can be saved with the proposed diagnostic system based on electrical resistance estimation. Full article

This paper presents the initial steps taken in analysing the benefits of connected autonomous vehicles (CAVs), especially Modular Autonomous Vehicles (MAVs), in search of sustainable solutions for reducing energy consumption per passenger in air transport. For this particular case, a Mobility-as-a-Service (MaaS) solution is proposed, correlating airside transport with landside transport, as an urban mobility alternative. To better understand the benefits of the proposal, this paper studies the impact on energy consumption conceptual differences between a conventional public transport fleet using Battery Electric Buses (BEBs) and an MAV fleet. Simulations for simple public transport tasks are performed to highlight the advantages of the modular vehicle concept, in which routes are assigned dynamically based on the requested passenger carrying capacity and travel distance, aiming to optimize the efficiency of the entire system. With a proven reduction in energy consumption due to better use of available passenger capacity and reduced travel times in which the vehicle is driving with a number of passengers less than half of its capacity, the concept can be addressed further in developing a predictive system that processes public transport data and delivers an optimized schedule for the entire fleet. The main goal being to improve overall operational efficiency and total cost of ownership, the second part of the paper studies the impact of weight distribution on efficiency parameters such as energy consumption, range, and overall performance of an electric bus. The impact on dynamic elements such as acceleration, braking, and cornering performance is analyzed, to assess the viability and safety of all types of electric bus operations. Full article

With the advancement of power systems, the integration of a substantial portion of renewable energy often leads to frequent voltage surges and increased fluctuations in distribution networks (DNs), significantly affecting the safety of DNs. Active distribution networks (ADNs) can address voltage issues arising from a high proportion of renewable energy by regulating distributed controllable resources. However, the conventional mathematical optimization-based approach to voltage reactive power control has certain limitations. It heavily depends on precise DN parameters, and its online implementation requires iterative solutions, resulting in prolonged computation time. In this study, we propose a Volt-VAR control (VVC) framework in ADNs based on multi-agent reinforcement learning (MARL). To simplify the control of photovoltaic (PV) inverters, the ADNs are initially divided into several distributed autonomous sub-networks based on the electrical distance of reactive voltage sensitivity. Subsequently, the Multi-Agent Soft Actor-Critic (MASAC) algorithm is employed to address the partitioned cooperative voltage control problem. During online deployment, the agents execute distributed cooperative control based on local observations. Comparative tests involving various methods are conducted on IEEE 33-bus and IEEE 141-bus medium-voltage DNs. The results demonstrate the effectiveness and versatility of this method in managing voltage fluctuations and mitigating reactive power loss. Full article

Intelligent transportation systems enhance the potential for sustainable, user-friendly, and efficient transport. By eliminating driver costs, autonomous buses facilitate the redesign of networks, timetables, and fleet structure in a cost-effective manner. The electrification of bus fleets offers the opportunity to further improve the environmental sustainability of transportation networks, but requires adjustments to vehicle schedules due to the limited range and charging requirements. This paper examines the intricate relationship between electrification and autonomous buses. To this end, timetables for autonomous electric buses of different sizes were developed for a real bus route in Aachen, Germany. The resulting electric vehicle scheduling problem was then solved using an adaptive large neighborhood search to determine the number of vehicles needed and the total cost of ownership. By eliminating driver costs, vehicles with lower passenger capacity become much more attractive, albeit at a slightly higher cost. In comparison, the incremental costs of electrification are low if the right approach is taken. Fluctuations in typical passenger numbers can be used to modify timetables and vehicle schedules to accommodate the charging needs of autonomous electric buses. In particular, electric bus concepts with fewer charging stations and lower charging power benefit from adapting the timetable to passenger numbers. The results demonstrate that the specific requirements of electric buses should be considered when adapting networks and timetables in order to design a sustainable transport network. Full article

Public transportation systems, including trams and buses, play a crucial role in urban traffic. However, these traditional modes of transport have some well-known drawbacks, such as long distances between stops, lengthy waiting times, and a lack of privacy. In response to these challenges, an innovative mobility concept called “FLAIT-train” offers potential solutions. The FLAIT-train operates on regular roads and aims to provide DOOR-2-DOOR transport, addressing the issues associated with fixed stops and offering increased accessibility and convenience. In its initial phase, the FLAIT-train operates on exclusive lanes, but it is designed to integrate with other traffic eventually. The vehicle technology of FLAIT-trains closely resembles that of battery electric autonomous vehicles. To assess whether FLAIT-trains can be used as a suitable alternative to conventional public transportation systems, this paper employs traffic simulations that consider key performance indicators, including the average waiting time per passenger, maximum waiting time of a single passenger, average in-vehicle time per passenger, and average occupancy rate of the vehicles. Using SUMO software (“Simulation of Urban Mobility”, version 1.12.0), a night bus service scenario is meticulously designed and generated. Within this scenario, both FLAIT-trains and conventional buses are simulated under identical conditions and based on statistical data. Full article

Electric power networks face vulnerabilities from various hazards, including extreme weather and natural disasters, resulting in prolonged outages and service disruptions. This paper proposes prosumer-centric networked electrical microgrids as a solution. EMGs integrate DERs, like SPV panels, WTs, BESSs, and BEVs, to form autonomous microgrids capable of operating independently during grid disruptions. The SMA was used to identify the appropriate allocation of DERs and BEVs to improve the resilience of the system. Prosumers, acting as both producers and consumers, play a crucial role by generating and sharing electricity within the microgrid. BEVs act as mobile energy storage units during emergencies. Load management and demand response strategies prioritize the energy needs for essential facilities, ensuring uninterrupted operation during adverse weather. Robust communication and control systems improve the emergency coordination and response. The resilience analysis focused on two case studies: moderate and severe damage, both under varying weather conditions. Simulations and experiments assessed the microgrid performance with different levels of DERs and demand. By testing on the IEEE 69-bus RDS, evaluated the EMGs’ strengths and limitations, demonstrating their potential to enhance distribution grid resilience against natural disasters. Full article

The novel contribution of this research is decentralised IOTA-based concepts of digital trust for securing remote driving in an urban environment. The conceptual solutions are studied and described, and respective experimental solutions are developed relying on digital identities, public key cryptography with a decentralised approach using decentralised identifiers (DIDs) and verifiable credentials (VCs), and an IOTA-based distributed ledger. The provided digital trust solutions were validated by executing them according to the remote driving scenario but with a simulated vehicle and simulated remote driving system. The hybrid simulation mainly focused on the validation of functional, causal temporal correctness, feasibility, and capabilities of the provided solutions. The evaluations indicate that the concepts of digital trust fulfil the purpose and contribute towards making remote driving more trustable. A supervisory stakeholder was used as a verifier, requiring a set of example verifiable credentials from the vehicle and the remote driver, and accepting them to the security control channel. The separation of control and data planes from each other was found to be a good solution because the delays caused by required security control can be limited to the initiation of the remote driving session without causing additional delays in the actual real-time remote driving control data flow. The application of the IOTA Tangle as the verifiable data registry was found to be sufficient for security control purposes. During the evaluations, the need for further studies related to scalability, application of wallets, dynamic trust situations, time-sensitive behaviour, and autonomous operations, as well as smart contract(s) between multiple stakeholders, were detected. As the next step of this research, the provided digital trust solutions will be integrated with a vehicle, remote driving system and traffic infrastructure for evaluation of the performance, reliability, scalability, and flexibility in real-world experiments of remote driving of an electric bus in an urban environment. Full article

The importance of vehicle security has increased in recent years in the automotive field, drawing the attention of both the industry and academia. This is due to the rise in cybersecurity threats caused by (1) the increase in vehicle connectivity schemes, such as the Internet of Things, vehicle-to-x communication, and over-the-air updates, and (2) the increased impact of such threats because of the added functionalities that are controlled by vehicle software. These causes and threats are further amplified in autonomous vehicles, which are generally equipped with more electronic control units (ECUs) that are connected through controller area networks (CANs). Due to the holistic nature of CANs, attacks on the networks can affect the functionality of all vehicle ECUs and the whole system. This can lead to a breach of privacy, denial of services, alteration of vehicle performance, and exposure to safety threats. Although cryptographic encryption and authentication algorithms and intrusion detection systems (IDS) are currently being used to detect and prevent CAN bus attacks, they have certain limitations. Therefore, this study proposed a mitigation scheme that can detect and prevent such attacks at the ECU level, which could address the limitations of existing algorithms. This study proposed the usage of a secure boot scheme to detect and prevent the execution of malicious codes, as the presence of one or more ECUs with a malicious code is the root cause of most CAN bus attacks. Secure boot schemes apply cryptographic data integrity algorithms to ensure that only authentic and untampered software can run on the vehicle’s ECUs. The selection of an appropriate cryptographic algorithm is important because it affects the secure boot schemes’ security level and performance. Therefore, this study also tested and compared the performance of the proposed secure boot scheme with five different data security algorithms implemented using the hardware security module (HSM) of the TC399 32-bit AURIX™ TriCore™ microcontroller through an electric autonomous vehicle’s control unit. The tests showed that the two most favorable schemes with the selected hardware are the secure boot scheme with the cipher-based message authentication code (CMAC), because it possesses the highest performance with an execution rate of 26.07 (ms/MB), and the secure boot scheme with the elliptic curve digital signature algorithm (ECDSA), because it provides a higher security level with an acceptable compromise in speed. This study also introduced and tested a novel variation of the ECDSA algorithm based on the CMAC algorithm, which was found to have a 19% performance gain over the standard ECDSA-based secure boot scheme. Full article

Autonomous mini-buses are low-cost passenger vehicles that travel along designated routes in industrial parks. In order to achieve this goal, it is necessary to implement functionalities such as lane-keeping and obstacle avoidance. To address the challenge of deploying deep learning algorithms to detect environmental information on low-performance computing units, which leads to difficulties in model deployment and the inability to meet real-time requirements, a lightweight algorithm called YOLOP-E based on the YOLOP algorithm is proposed. (The letter ‘E’ stands for EfficientNetV2, and YOLOP-E represents the optimization of the entire algorithm by replacing the backbone of the original model with EfficientNetV2.) The algorithm has been optimized and improved in terms of the following three aspects: Firstly, the YOLOP backbone network is reconstructed using the lightweight backbone network EfficientNet-V2, and depth-wise separable convolutions are used instead of regular convolutions. Secondly, a hybrid attention mechanism called CABM is employed to enhance the model’s feature-representation capability. Finally, the Focal EIoU and Smoothed Cross-Entropy loss functions are utilized to improve detection accuracy. YOLOP-E is the final result after the aforementioned optimizations are completed. Experimental results demonstrate that on the BDD100K dataset, the optimized algorithm achieves a 3.5% increase in mAP50 and a 4.1% increase in mIoU. During real-world vehicle testing, the detection rate reaches 41.6 FPS, achieving the visual perception requirements of the autonomous shuttle bus while maintaining a lightweight design and improving detection accuracy. Full article

Currently, operating electrical power systems (EPS) is a complex task that relies on the experience of the operators or the strength of algorithms developed for autonomous operation. The continuous operation of EPS is vulnerable to intentional cybernetic and physical attacks. With the most significant extension and distribution in the EPS, the transmission lines are most exposed to potential attacks. Before this, the entire behavior of the EPS changes, and, on occasions, a blackout can even be generated. The present investigation focused on developing a methodology for reconfiguring the power system against intentional attacks, considering the topology change through optimal switching of transmission lines (OTS) based on optimal DC flows and quantifying the contingency index, which allows for the identification of the weaknesses of the EPS. The methodology was applied to the IEEE 30−bus system, and contingencies were randomly generated, as is typical with intentional attacks. The study successfully identified the reconfiguration strategy of EPS based on OTS-DC, mitigating potential problems such as line loadability and voltage angle deviation in the nodes. Full article

Urban mobility scenarios are constantly evolving, and today’s solutions may not be adequate in the future. Through innovative analysis and design methods encapsulated by the IDeS methodology, it is possible to plausibly hypothesize a number of key scenarios to be analyzed, for which vehicles can be designed in order to solve the main problems. Scenarios such as the steady growth in public mobility, based on the sharing of electric mini-buses at the expense of the privatization of the means of transport, lead to the gradual rethinking of citizens’ needs and the supporting infrastructure. Problems such as the lack of privacy of public vehicles, the efficiency of the infrastructure and recharging modes of e-buses, and autonomous driving are addressed here through methods such as QFD (quality function deployment) and SDE (stylistic design engineering), with the aim of outlining a proposal that, to date, is futuristic but is designed to be concrete and feasible within the next decade. These methodologies were applied to the design of a sustainable urban transport system consisting of an electric mini-bus, effected by rethinking the layout of the interior spaces in favor of areas enabling greater privacy and a mobile recharging system (MBS) capable of offering a new management strategy for the non-stop recharging phase. Through the use of an MBS, which functions as a mobile ‘energy bank’ module that is capable of autonomously reaching a mini-bus in need of recharging and extending its autonomy by connecting and recharging it, the proposed system can potentially be enabled to perform its required service during the day without any need to spend time making intermediate stops for the purpose of recharging. Full article

The increasing prevalence and severity of wildfires, severe storms, and cyberattacks is driving the introduction of numerous microgrids to improve resilience locally. While distributed energy resources (DERs), such as small-scale wind and solar photovoltaics with storage, will be major components in future microgrids, today, the majority of microgrids are backed up with fossil-fuel-based generators. Small modular reactors (SMRs) can form synergistic mix with DERs due to their ability to provide baseload and flexible power. The heat produced by SMRs can also fulfill the heating needs of microgrid consumers. This paper discusses an operational scheme based on distributed control of flexible power assets to strengthen the operational resilience of SMR-DER integrated-energy microgrids. A framework is developed to assess the operational resilience of SMR-DER microgrids in terms of system adaptive real-power capacity quantified as a response area metric (RAM). Month-long simulation results are shown with a microgrid developed in a modified Institute of Electrical and Electronics Engineers (IEEE)-30 bus system. The RAM values calculated along the operational simulation reflect the system resilience in real time and can be used to supervise the microgrid operation and reactor’s autonomous control. Full article

The increased popularity of small-scale DER has replaced the well-established concept of conventional generating plants around the world. In the present energy scenario, a significant share of energy production now comes from the grid integrated DERs installed at various consumer premises. These DERs are being renewable-based generates only intermittent power, which in turn makes the scheduling of electrical dispatch a tough task. The Virtual Power Plant (VPP) is a potential solution to this challenge, which coordinates and aggregates the DERs generation into a single controllable profile. In this paper, a modified PSO-based multi-objective optimization is proposed for the VPP scheduling in distribution network applications such as energy cost minimization, peak shaving, and reliability improvement. For feasibility analysis of the VPP, a case study of state power utility is taken, which includes a 90 bus industrial feeder with grid integrated PVs as DER. The optimized results are computed in both grid-connected and autonomous mode reveal that the operating cost, peak demand, and EENS are declined by 31.70%, 23.59%, and 62.30% respectively. The overall results obtained are compared by the results obtained from other well-established optimization techniques and it is found that the proposed technique is comparatively more cost-effective than others. Full article