Browse Topic: Engine components
A glow plug is generally used to assist the starting of diesel engines in cold weather condition. Low ambient temperature makes the starting of diesel engine difficult because the engine block acts as a heat sink by absorbing the heat of compression. Hence, the air-fuel mixture at the combustion chamber is not capable of self-ignition based on air compression only. Diesel engines do not need any starting aid in general but in such scenarios, glow plug ensures reliable starting in all weather conditions. Glow plug is actually a heating device with high electrical resistance, which heats up rapidly when electrified. The high surface temperature of glow plug generates a heat flux and helps in igniting the fuel even when the engine is insufficiently hot for normal operation. Durability concerns have been observed in ceramic glow plugs during testing phases because of crack formation. Root cause analysis is performed in this study to understand the probable reasons behind cracking of the
Internal combustion engines (ICEs) will continue to be critical propulsion systems for certain applications in the coming decades. It is, therefore, extremely important to further develop environmentally friendly and sustainable internal combustion engines. These developments include, but are not limited to, improved tribology and reduced mechanical losses, higher mean effective pressures, compatibility with carbon-free or -neutral fuels, improved exhaust gas aftertreatment systems, and condition-based maintenance. Due to the increased stress on engine components associated with these changes, accurate, online data with high temporal resolution is required from inside the engine. Acquisition of this data can be achieved with a wireless telemetry system in order to minimize the influence of measurement devices on the measurement itself. This paper describes challenges in the development of telemetry systems for internal combustion engines. Systems for measuring the piston temperature
This paper presents an advanced control system design for an engine cooling system in an internal combustion engine (ICE) vehicle. Building upon our previous work, we have derived models for crucial temperatures within the engine, including combustion wall temperature, coolant-out temperature, block temperature, as well as temperatures in external components such as heat exchangers and radiator. To accurately predict these temperatures in a rapid manner, we have utilized a lumped parameter concept with a mean-value approach. This approach allows for precise temperature estimation while maintaining computational efficiency. Given the complexity of the cooling system, we have proposed a linear time-varying (LTV) model predictive control (MPC) system to regulate the temperatures. This control system linearizes the model at each time step and applies linear MPC over the control and prediction horizons. By doing so, we effectively control the highly nonlinear and time-delayed system
Structural topology optimization for vehicle structures under static loading is a well-established practice. Unfortunately, extending these methods to components subjected to dynamic loading is challenged by the absence of sensitivity coefficients: analytical expressions are unavailable and numerical approximations are computationally impractical. To alleviate this problem, researchers have proposed methods such as hybrid cellular automata (HCA) and equivalent static load (ESL). This work introduces a new approach based on equivalent static displacement (ESD). The proposed ESD method uses a set of prescribed nodal displacements, simulating the resultant reaction forces of a body subjected to dynamic loading, at different simulation time steps to establish the boundary conditions for each corresponding model—one model for each simulation time. A scalarized multi-objective function is defined considering all the models. A gradient-based optimizer is incorporated to find the optimal
A hierarchical control architecture is commonly employed in hybrid torque control, where the supervisor CPU oversees system-level objectives, while the slave CPU manages lower-level control tasks. Frequently, control authority must be transferred between the two to achieve optimal coordination and synchronization. When a closed-loop component is utilized, accurately determining its actual contribution to the controlled system can be challenging. This is because closed-loop components are often designed to compensate for unknown dynamics, component variations, and actuation uncertainties. This paper presents a novel approach to closed-loop component factor transfer and coordination between two CPUs operating at different hierarchical levels within a complex system. The proposed framework enables seamless control authority transition between the supervisor and slave CPUs, ensuring optimal system performance and robustness. To mitigate disturbances and uncertainties during the transition
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