Measurement Data HCCI and SI with Gasoline and Ethanol

This dataset contains comprehensive measurement data from a single cylinder HCCI (Homogeneous Charge Compression Ignition) research engine test bench. The experiments were conducted to investigate various operating strategies and fuel blends, with a focus on advanced combustion concepts and real-time control approaches. The dataset includes the following measurement series: HCCI Operating Maps: Systematic variation of negative valve overlap and injection duration was performed to generate HCCI operating maps using gasoline (selected points) and ethanol as fuels. SI Operation Reference Points: Comparable load points in conventional spark ignition (SI) mode were recorded with both gasoline and ethanol. Reference Motored Measurements: Baseline motored measurements (engine driven without combustion) were taken at several time points to monitor system drift and repeatability. HCCI with Ethanol-Water Blends: Detailed HCCI measurements were carried out using ethanol-based fuels with water admixtures of 0%, 5%, 10%, 15%, 20%, and 25%. For each blend, three stationary operating points and approximately fifteen dynamic operating points are included; in the dynamic cases, actuator setpoints were systematically varied. RL-Controlled Dynamic HCCI Points: Two dynamic HCCI operation points with gasoline are included where a reinforcement learning agent tracked load transients—one during training phase, one after convergence. For each operating point, between 500 and 1000 consecutive engine cycles were recorded. The raw data comprises cycle-resolved in-cylinder pressure traces, individual-cycle emissions data, as well as stationary values for all relevant parameters such as pressures, temperatures, emission concentrations, mass flows, etc. These stationary signals are available either as mean values per measurement point or as continuous time series sampled at 10 Hz. A documentation file accompanies every dataset. It provides metadata for every measurement point including experimental conditions, actuator settings, fuel composition details, sensor specifications and calibration status. This dataset enables in-depth analysis of advanced combustion phenomena under varied fuel compositions and control strategies. It supports research on cycle-to-cycle variability, transient behavior in HCCI engines, effects of water addition to ethanol fuel blends, comparison between SI and HCCI operation modes, and the application of machine learning methods for engine control.