Browse Topic: Electronic control systems
Due to the high-power density, high torque rating, low torque ripples and fault-tolerant capability, the Dual Three-Phase Permanent Magnet Synchronous Motor (DTP-PMSM) has recently emerged as a feasible alternative for automotive applications. However, it comes with its own challenge of increased losses at low torque due to the use of 6-phase inverter or two three-phase inverters. The DTP-PMSM drive model can be designed to function in two operating modes, double-channel (dual three-phase) mode with both the inverters operating, and single-channel (three-phase) with one of the two inverters shut down. This paper proposed an efficiency analysis between single channel and double channel modes in a DTP-PMSM drive. A simulation model is prepared to calculate efficiency, and the losses associated with different parts of battery fed DTP-PMSM drive system operated in both modes. Detailed loss model is simulated to represent efficiency of a battery-fed DTP-PMSM drive system. Both single
The driving capability and charging performance of electric vehicles (EVs) are continuously improving, with high-performance EVs increasing the voltage platform from below 500V to 800V or even 900V. To accommodate existing low-voltage public charging stations, vehicles with high-voltage platforms typically incorporate boost chargers. However, these boost chargers incur additional costs, weight, and spatial requirements. Most mature solutions add a DC-DC boost converter, which results in lower charging power and higher costs. Some new methods leverage the power switching devices and motor inductance within the electric drive motor to form a boost circuit using a three-phase current in-phase control strategy for charging. This approach requires an external inductor to reduce charging current ripple. Another method avoids the use of an external inductor by employing a two-parallel-one-series topology to minimize current ripple; however, this reduces charging power and increases the risk
Software Defined Vehicle (SDV) is gaining attraction in the automotive industry due to its wide range of benefits like remote software/feature upgrade, scalable functionality, Electronic Control Unit (ECU) commonization, remote diagnostics, increased safety, etc. To obtain all these benefits, ECUs need to be designed accordingly. ECU hardware must be designed to support a range of vehicles with a variety of loading, scalable features, power distribution, levels of processing, and networking architecture. Each domain has unique challenges to make the ECU economical and robust to operating conditions without compromising performance. This paper illustrates the critical hardware design challenges to accommodate a scalable SDV architecture. This paper focuses electrical interface design to support wide range of input/output port loads, scalable functionality, and robust diagnostics. Also, flexibility of microprocessor processing capability, ECU networking, and communication complexity are
As automotive technology advances, modern vehicles increasingly rely on complex electronics such as cameras, sensors, radar and lidar. These components are critical for advanced driver-assistance systems (ADAS) and automated driving. With the growing complexity of these systems, automotive manufacturers face challenges in efficiently transmitting both power and data while minimizing weight and system complexity. Power over Coaxial (PoC) technology offers a solution by allowing the transmission of power and data over a single coaxial cable, significantly simplifying vehicle design. With the integration of more electronic systems, especially those required for ADAS and autonomous driving, the demand for power and high-speed data transmission in vehicles has surged. Modern cars now use multiple cameras and sensors, and as vehicle systems continue to evolve, the number of electronic components is expected to increase. This shift places significant demands on the transmission of both data
The advancement of the automotive industry towards automation has fostered a growing integration between this field and automation. Future projects aim for the complete automation of the act of driving, enabling the vehicle to operate independently after the driver inputs the desired destination. In this context, the use of simulation systems becomes essential for the development and testing of control systems. This work proposes the control of an autonomous vehicle through fuzzy logic. Fuzzy logic allows for the development of sophisticated control systems in simple, easily maintainable, and low-cost controllers, proving particularly useful when the mathematical model is subject to uncertainties. To achieve this goal, the PDCA method was adopted to guide the stages of defining the problem, implementation, and evaluation of the proposed model. The code implementation was done in Python and validated using different looping scenarios. Three linguistic variables were used, one with three
Heavy-duty vehicles, particularly those towing higher weights, require a continuous/secondary braking system. While conventional vehicles employ Retarder or Engine brake systems, electric vehicles utilize recuperation for continuous braking. In a state where HV Battery is at 100% of SOC, recuperated energy from vehicle operation is passed on to HPR and it converts electrical energy into waste heat energy. This study focuses on identification of routes which are critical for High Power Brake Resistors (HPRs), by analyzing the elevation data of existing charging stations, the route’s slope distribution, and the vehicle’s battery SOC. This research ultimately suggests a method to identify HPR critical vehicle operational routes which can be useful for energy efficient route planning algorithms, leading to significant cost savings for customers and contributing to environmental sustainability.
Emergence of Software Defined Vehicles (SDVs) presents a paradigm shift in the automotive domain. In this paper, we explore the application of Model-Based Systems Engineering (MBSE) for comprehensive system simulation within the SDV architecture. The key challenge for developing a system model for SDV using traditional methods is the document centric approach combined with the complexity of SDV. This MBSE approach can help to reduce the complexity involved in Software-Defined Vehicle Architecture making it more flexible, consistent, and scalable. The proposed approach facilitates the definition and analysis of functional, logical, and physical architecture enabling efficient feature and resource allocation and verification of system behaviour. It also enables iterative component analysis based on performance parameters and component interaction analysis (using sequence diagrams).
In the rapidly evolving field of automotive engineering, the drive for innovation is relentless. One critical component of modern vehicles is the automotive ECU. Ensuring the reliability and performance of ECU is paramount, and this has led to the integration of advanced testing methodologies such as Hardware-in-the-Loop (HIL) testing. In conjunction with HIL, the adoption of Continuous Integration (CI) and Continuous Testing (CT) processes has revolutionized how automotive ECU are developed and validated. This paper explores the integration of CI and CT in HIL testing for automotive ECU, highlighting the benefits, challenges, and best practices. Continuous Integration and Continuous Test (CI/CT) are essential practices in software development. Continuous Integration process involves regularly integrating code changes into the main branch, ensuring that it does not interfere with the work of other developers. The CI/CT server automatically build and test code whenever a new commit is
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