CARISSMA Institute of Electric, Connected and Secure Mobility (C-ECOS)
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Lithium-Ion Batteries (LIBs) usually present several degradation processes, which include their complex Solid-Electrolyte Interphase (SEI) formation process, which can result in mechanical, thermal, and chemical failures. The SEI layer is a protective layer that forms on the anode surface. The SEI layer allows the movement of lithium ions while blocking electrons, which is necessary to prevent short circuits in the battery and ensure safe operation. However, the SEI formation mechanisms reduce battery capacity and power as they consume electrolyte species, resulting in irreversible material loss. Furthermore, it is important to understand the degradation reactions of the LIBs used in Electric Vehicles (EVs), aiming to establish the battery lifespan, predict and minimise material losses, and establish an adequate time for replacement. Moreover, LIBs applied in EVs suffer from two main categories of degradation, which are, specifically, calendar degradation and cycling degradation. There are several studies about battery degradation available in the literature, including different degradation phenomena, but the degradation mechanisms of large-format LIBs have rarely been investigated. Therefore, this review aims to present a systematic review of the existing literature about LIB degradation, providing insight into the complex parameters that affect battery degradation mechanisms. Furthermore, this review has investigated the influence of time, C-rate, depth of discharge, working voltage window, thermal and mechanical stresses, and side reactions in the degradation of LIBs.
Cooperative intelligent transport systems (C-ITSs) are mass-produced and sold in Europe, promising enhanced safety and comfort. Direct vehicle communication, known as vehicle-to-everything (V2X) communication, is crucial in this context. Drivers receive warnings about potential hazards by exchanging vehicle status and environmental data with other communication-enabled vehicles. However, the impact of these warnings on drivers and their inclusion in accident reconstruction remains uncertain. Unlike sensor-based warnings, V2X warnings may not provide a visible reason for the alert, potentially affecting reaction times and behavior. In this work, a simulator study on V2X warnings was conducted with 32 participants to generate findings on reaction times and behavior for accident reconstruction in connection with these systems. Two scenarios from the Car-2-Car Communication Consortium were implemented: “Stationary Vehicle Warning—Broken-Down Vehicle” and “Dangerous Situation—Electronic Emergency Brake Lights”. Volkswagen’s warning concept was utilized, as they are the sole provider of cooperative vehicles in Europe. Results show that V2X warnings without visible reasons did not negatively impact reaction times or behavior, with average reaction times between 0.58 s (steering) and 0.69 s (braking). No significant distraction or search for warning reasons was observed. However, additional information in the warnings caused confusion and was seldom noticed by subjects. In this study, participants responded correctly and appropriately to the shown false-positive warnings. A wrong reaction triggering an accident is possible but unlikely. Overall, V2X warnings showed no negative impacts compared with sensor-based systems. This means that there are no differences in accident reconstruction regarding the source of the warning (sensors or communication). However, it is important that it is known that there was a warning, which is why the occurrence of V2X warnings should also be saved in the EDR in the future.
We examine the impact of water (160 ± 41 ppm of reference) on the anode, cathode, separator and electrolyte in two aging scenarios: calendric aging (60 °C, 80 days, charged state), resulting in a triggered current interrupt device (CID), and cycling 1680 times (charge/discharge with 1C, 2.75–4.2 V, 20 ± 2 °C), resulting in 24.5% residual capacity. We applied computer tomography (CT), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and secondary ion mass spectrometry (SIMS) to understand the capacity loss. The aged NMC/LCO–graphite cells were compared to a reference cell in pristine state. Both aging scenarios showed (a) thick depositions on the anode and cathode consisting mainly of oxygen, fluorine and phosphorous, (b) reduced separator pore sizes, (c) the deposition of Mn, Co and Ni on top of the anode and (d) the decomposition of the conductive salt LiPF6 accompanied by HF formation and a loss of active lithium. Calendric aging consumes the water content and additionally leads to (e) the decomposition of the organic solvent followed by CO2 gas formation. Cyclic aging increases the water content and additionally results in (f) the consumption of the additive fluoroethylene carbonate (FEC). These findings show how water affects aging phenomena and results in a capacity decrease in the cell.
Fused Deposition Modeling (FDM) is a well-established manufacturing method for producing both prototype and functional components. This study investigates the mechanical properties of FDM components by material and process-related influencing variables. Tensile tests were conducted on seven different materials in their raw filament form, two of which were fiber-reinforced, to analyze their material-related influence. To cover a wide range from standard to advanced materials relevant for load-carrying components as well as their respective variations, polylactic acid (PLA), 30% wood-fiber-reinforced PLA, acrylonitrile butadiene styrene (ABS), polycarbonate (PC), a blend of ABS and PC, Nylon, and 30% glass-fiber-reinforced Nylon were selected. The process-related influencing variables were studied using the following process parameters: layer thickness, nozzle diameter, build orientation, nozzle temperature, infill density and pattern, and raster angle. The first test series revealed that the addition of wood fibers significantly worsened the mechanical behavior of PLA due to the lack of fiber bonding to the matrix and significant pore formation. The polymer blend of ABS and PC only showed improvements in stiffness. Significant strength and stiffness improvements were found by embedding glass fibers in Nylon, despite partially poor fiber–matrix bonding. The materials with the best properties were selected for the process parameter analysis. When examining the impact of layer thickness on part strength, a clear correlation was evident. Smaller layer thicknesses resulted in higher strength, while stiffness did not appear to be affected. Conversely, larger nozzle diameters and lower nozzle temperatures only positively impacted stiffness, with little effect on strength. The part orientation did alter the fracture behavior of the test specimens. Although an on-edge orientation resulted in higher stiffness, it failed at lower stresses. Higher infill densities and infill patterns aligned with the load direction led to the best mechanical results. The raster angle had a significant impact on the behavior of the printed bodies. An alternating raster angle resulted in lower strengths and stiffness compared to a unidirectional raster angle. However, it also caused significant stretching due to the rotation of the beads.
Among the possible traffic members on a Vehicle-to-Everything network, the term Vulnerable Road User (VRU) is assigned e.g. to pedestrians and cyclists. The VRU Awareness Message (VAM) is used by VRUs to inform other users of their presence and ensure they are perceived in a traffic system. Since the number of VRUs in crowded areas might be very high, the over-the-air traffic might be overloaded. To reduce channel overload, VAMs offer a clustering feature in which VRUs with similar kinematics and positions can group themselves so that only one device transmits messages. The VRU Basic Service specification describes the cluster as a bounding box that must cover all its members using a geometric shape so that other vehicles in the vicinity can avoid colliding with the contained VRUs. This paper contributes to the standardization effort by introducing a data structure, the Cluster Map, for the clustering in the VRU Basic Service. Furthermore, this work is the first to suggest strategies for forming bounding box shapes. Simulation results show that each of the geometry types is useful in different situations, thus further research on the topic is advised.
Cooperative Intelligent Transportation Systems have achieved a mature technology stage and are in an early phase of mass deployment in Europe. Relying on Vehicle-to-X communication, these systems were primarily developed to improve traffic safety, efficiency, and driving comfort. However, they also offer great opportunities for other use cases. One of them is forensic accident analysis, where the received data provide details about the status of other traffic participants, give insights into the accident scenario, and therefore help in understanding accident causes. A high accuracy of the sent information is essential: For safety use cases, such as traffic jam warning, a poor accuracy of the data may result in wrong driver information, undermine the usability of the system and even create new safety risks. For accident analysis, a low accuracy may prevent the correct reconstruction of an accident. This paper presents an experimental study of the first generation of Cooperative Intelligent Transportation Systems in Europe. The results indicate a high accuracy for most of the data fields in the Vehicle-to-X messages, namely speed, acceleration, heading and yaw rate information, which meet the accuracy requirements for safety use cases and accident analysis. In contrast, the position data, which are also carried in the messages, have larger errors. Specifically, we observed that the lateral position still has an acceptable accuracy. The error of the longitudinal position is larger and may compromise safety use cases with high accuracy requirements. Even with limited accuracy, the data provide a high value for the accident analysis. Since we also found that the accuracy of the data increases for newer vehicle models, we presume that Vehicle-to-X data have the potential for exact accident reconstruction.