Browse Topic: Tests and Testing

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For regions with cold climate, the range of an electric bus becomes a serious restriction to expanding the use of this type of transport. Increased energy consumption affects not only the autonomous driving range, but also the service life of the batteries, the schedule delays and the load on the charging infrastructure. The aim of the presented research is to experimentally and computationally determine the energy consumption for heating the driver's cabin and passenger compartment of an electric bus during the autumn-winter operation period, as well as to identify and analyze ways to reduce this energy consumption. To determine the air temperature in the passenger compartment, a mathematical model based on heat balance equations was used. This model was validated using data from real-world tests. The research was conducted at a proving ground under two conditions: driving at a constant speed and simulating urban bus operation with stops and door openings. The causes of heat loss in
Kozlov, AndreyTerenchenko, AlexeyStryapunin, Alexander
This study is conducted to analyse the significance of the Bharat NCAP crash test protocol in real road crashes in India. Accident data from on-the-spot investigation (Road Accident Sampling System India) and Government of India’s, Ministry of Road Transport and Highways official road accident statistics 2023 is used together to understand the real road accidents in India. The current Bharat NCAP crash test protocol is compared against the real road accidents and the frequency of the same in discussed in this paper. A seven-step calculation method is developed to analyse real accidents together with existing crash tests by using similar crash characteristics like impact area, overlap and direction of force. This method makes the real accident comparable with the corresponding crash test by calculating the impact energy during the collision between the real accident and a collision under crash test conditions. Relevant parameters in real accidents that significantly influence the test
Moennich, JoergLich, ThomasKumaresh, Girikumar
Highway Pilot (HWP) systems, classified as SAE Level 3 Automated Driving Systems (ADS), represent a potential advancement for safer and more efficient highway drives. In this work, the development of a connected HWP prototype is presented. The HWP system is deployed in a real test vehicle and designed to operate autonomously in highway environments. The implementation presented in this paper covers the complete setup of the vehicle platform, including sensor selection and placement, hardware integration and communication interfaces for both autonomous functionality and Vehicle-to-Everything (V2X) connectivity. The software architecture follows a modular design, composed of modules for perception, decision-making and motion control to operate in real-time. The prototype integrates Vehicle-to-Vehicle (V2V) communication, such as Cooperative Awareness Messages (CAM), to enhance situational awareness and improve the overall system behaviour. The modular structure allows new functionalities
Domingo Mateu, BernatLeiva Ricart, GiselaFacerias Pelegri, MarcPerez, Marc
This paper examines the challenges and opportunities in homologating AI-driven Automated Driving Systems (ADS). As AI introduces dynamic learning and adaptability to vehicles, traditional static homologation frameworks are becoming inadequate. The study analyzes existing methodologies, such as the New Assessment/Test Methodology (NATM), and how various institutions address AI incorporation into ADS certification. Key challenges identified include managing continuous learning, addressing the "black-box" nature of AI models, and ensuring robust data management. The paper proposes a harmonized roadmap for AI in ADS homologation, integrating safety standards like ISO/TR 4804 and ISO 21448 with AI-specific considerations. It emphasizes the need for explainability, robustness, transparency, and enhanced data management in certification processes. The study concludes that a unified, global approach to AI homologation is crucial, balancing innovation with safety while addressing ethical
Lujan Tutusaus, CarlosHidalgo, Justin
Aluminum foils have gained traction with EV battery manufacturers for their pouch cell format. Over the years, it has evolved as a material of choice, but it is still plagued by the issues of stress concentration and swelling due to lower strength and lower stiffness of base aluminum layer. Preliminary investigation revealed that laminates using steel foil material (thickness < 0.1mm) could be a potential candidate for EV pouch cell casing. Thus, steel-based laminate was developed meeting key functional requirements (e.g., barrier performance, insulation resistance, peel strength, electrolyte resistance, formable without cracking at edges, and heat sealing compliant). This innovative patented steel-based laminate [1] was further used to manufacture pouch cell prototypes (up to a maximum capacity of 2.8Ah) for key performance evaluation (e.g., cell cycling and nail penetration). The study paves the way for a low cost, sustainable and flexible yet strong steel-based laminate packaging
Singh, Pundan KumarRaj, AbhishekKumar, AnkitChatterjee, SourabhVerma, Rahul KumarSamantaray, BikashGautam, VikasPandey, Ashwani
Final design choices are frequently made early in the product development cycle in the fiercely competitive automotive sector. However, because of manufacturing tolerances design tolerances stiffness element fitment and other noise factors physical prototypes might show variations from nominal specifications. Significant performance differences (correlation gaps) between the digital twin representation produced during the design phase and real-world performance may result from these deviations. Measuring every system parameter repeatedly to take these variations into account can be expensive and impractical. The goal of this study is to identify important system parameters from system characteristic data produced by controlled dynamic testing to close the gap between digital and physical models. Dynamic load cases are carried out with a 4-poster test rig where vehicle responses are captured under controlled circumstances at different suspension locations. An ideal set of digital model
Verma, Rahul RanjanGoli, Naga Aswani KumarPrasad, Tej Pratap
The work completed on “System level concepts to test and design integrated EV system involving power conversion to satisfy ISO26262 functional safety requirement” is included in the paper. Integrating power conversion and traction inverter subsystems in EVs is currently popular since it increases dependability and improves efficiency and cost-effectiveness. Maintaining safety standards is at danger due to the growing safety requirements, which also raise manufacturing costs and time. The three primary components of integrated EV systems are the PDU, DC-DC converter, and onboard charger. Every part and piece of software is always changing and needs to be tested and validated in an economical way. Since the failure of any one of these components could lead to a disaster, the article outlines the economical approaches and testing techniques to verify and guarantee that the system meets the functional safety criterion.
Uthaman, SreekumarMulay, Abhijit BGadekar, Pundlik
In India, Currently Continuous FULL MIDC (Modified Indian Driving Cycle) is used to declare the Range & Energy consumption of BEV (Battery Electric Vehicle). AISC (Automotive Industry Standards Committee) is looking to implement Worldwide Harmonized Light-Duty Test Procedure (WLTP) in India. AISC released AIS 175 for WLTP implementation from Apr 2027. The objective of WLTP is to standardize the test procedure globally for evaluating Emission/FE/Range of Light Duty Vehicles. But the effect of AIS 175 regulation on Battery Electric Vehicles Range Declaration is very less. The Range is almost same as Full MIDC declared Range. The On-road Range BEV is always lesser than the Declared Range of vehicles because of ambient conditions. Usually, the Full MIDC declared Range will be 20% ~26% higher than actual On Road Range. The Range of BEV as per India WLTP 3-Phase was observed 18% ~ 24% higher than actual On-road range of vehicles. There is only 2% difference observed between Full MIDC Range
Shiva Kumar, MucharlaTentu, Kavya
In recent times, a standard driving cycle is an excellent way to measure the electric range of EVs. This process is standardized and repeatable; however, it has some drawbacks, such as low active functions being tested in a controlled environment. This sometimes causes huge variations in the range between driving cycles and actual on-road tests. This problem of variation can be solved by on-road testing and testing a vehicle for customer-based velocity cycles. On-road measurement may be high on active functions while testing, which may give an exact idea of real-world consumption, but the repeatability of these test procedures is low due to excessive randomness. The repeatability of these cycles is low due to external factors acting on the vehicle during on-road testing, such as ambient temperature, driver behavior, traffic, terrain, altitude, and load conditions. No two measurements can have the same consumption, even if they are done on the same road with the same vehicle, due to the
Kelkar, KshitijKanakannavar, Rohit
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