Search Results

One of the challenges faced when using Li-ion batteries in electric vehicles is to keep the cell temperatures below a given threshold. Mathematical modeling would indeed be an efficient tool to test virtually this requirement and accelerate the battery product lifecycle. Moreover, temperature predicting models could potentially be used on-board to decrease the limitations associated with sensor based temperature feedbacks. Accordingly, we present a complete modeling procedure which was used to calculate the cell temperatures during a given electric vehicle trip. The procedure includes a simple vehicle dynamics model, an equivalent circuit battery model, and a 3D finite element thermal model. Model parameters were identified from measurements taken during constant current and pulse current discharge tests. The cell temperatures corresponding to an actual electric vehicle trip were calculated and compared with measured values.

Gasoline Controlled Auto-Ignition (GCAI) combustion, which can be categorized under Homogeneous Charge Compression Ignition (HCCI), is a low-temperature combustion process with promising benefits such as ultra-low cylinder-out NOx emissions and reduced brake-specific fuel consumption, which are the critical parameters in any modern engine. Since this technology is based on uncontrolled auto-ignition of a premixed charge, it is very sensitive to any change in boundary conditions during engine operation. Adopting real time valve timing and fuel-injection strategies can enable improved control over GCAI combustion. This work discusses the outcome of collaborative experimental research by the partnering institutes in this direction. Experiments were performed in a single cylinder GCAI engine with variable valve timing and Gasoline Direct Injection (GDI) at constant indicated mean effective pressure (IMEP). In the first phase intake and exhaust valve timing sweeps were investigated.

To comply with the new regulations on particulate matter emissions, the manufacturers of light-duty as well as heavy-duty vehicles more commonly use diesel particulate filters (DPF). The regeneration of DPF depends to a significant extent on the properties of the soot stored. Within the Cluster of Excellence "Tailor-Made Fuels from Biomass (TMFB)" at RWTH Aachen University, the Institute for Combustion Engines carried out a detailed investigation program to explore the potential of future biofuel candidates for optimized combustion systems. The experiments for particulate measurements and analysis were conducted on a EURO 6-compliant High Efficiency Diesel Combustion System (HECS) with petroleum-based diesel fuel as reference and a today's commercial biofuel (i.e., FAME) as well as a potential future biomass-derived fuel candidate (i.e., 2-MTHF/DBE). Thermo gravimetric analyzer (TGA) was used in this study to evaluate the oxidative reactivity of the soot.

During a thermal regeneration of a Diesel particulate filter (DPF) the temperature inside the DPF may raise above critical thresholds in an uncontrolled way (thermal shock). Especially driving conditions with a comparable low exhaust gas mass flow and high oxygen content like idle speed may create a thermal shock. This paper presents a concept for an ECU software structure to prevent the DPF from reaching improper temperatures and the methodology in order to calibrate this ECU structure. The concept deals in general with a closed-loop control of the exhaust gas air-fuel-ratio during the critical engine operation phases. Those critical operation phases are identified at the engine test bench during “Drop-to-Idle” and “Drop-to-Overrun” experiments. The experiments show that those phases are critical having on the one hand a low exhaust gas mass flow and on the other hand a high oxygen percentage in the exhaust gas.