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Biofuel can enable a sustainable transport solution and lower greenhouse gas emissions compared to standard fuels. This study focuses on biodiesel, implemented in the easiest way as drop in fuel. When mixing biodiesel into diesel one can run into problems with solubility causing contaminants precipitating out as insolubilities. These insolubilities, also called soft particles, can cause problems such as internal injector deposits and nozzle fouling. One way to overcome the problem of soft particles is by filtration. It is thus of great interest to be able to quantify fuel filters’ ability to intercept soft particles. The aim of this study is to test different fuel filters for heavy-duty engines and their ability to filter out synthetic soft particles. A custom-built fuel filter rig is presented, together with some of its general design requirements. For evaluation of the efficiency of the filters, fuel samples were taken before and after the filters.

This paper investigates the FPGA resources for the implementation of in-cycle closed-loop combustion control algorithms. Closed-loop combustion control obtains feedback from fast in-cylinder pressure measurements for accurate and reliable information about the combustion progress, synchronized with the flywheel encoder. In-cycle combustion control requires accurate and fast computations for their real-time execution. A compromise between accuracy and computation complexity must be selected for an effective combustion control. The requirements on the signal processing (evaluation rate and digital resolution) are investigated. A common practice for the combustion supervision is to monitor the heat release rate. For its calculation, different methods for the computation of the cylinder volume and heat capacity ratio are compared. Combustion feedback requires of virtual sensors for the misfire detection, burnt fuel mass and pressure prediction.

Improving turbocharger performance to increase engine efficiency has the potential to help meet current and upcoming exhaust legislation. One limiting factor is compressor surge, an air flow instability phenomenon capable of causing severe vibration and noise. To avoid surge, the turbocharger is operated with a safety margin (surge margin) which, as well as avoiding surge in steady state operation, unfortunately also lowers engine performance. This paper investigates the possibility of detecting compressor surge with a conventional engine knock sensor. It further recommends a surge detection algorithm based on their signals during transient engine operation. Three knock sensors were mounted on the turbocharger and placed along the axes of three dimensions of movement. The engine was operated in load steps starting from steady state. The steady state points of operation covered the vital parts of the engine speed and load range.

Typically, the combustion in an internal combustion engine is open-loop controlled. The introduction of a cylinder pressure sensor opens the possibility to introduce a virtual combustion sensor. This virtual sensor is a possible enabler for closed-loop combustion control and thus the possibility to counteract the effects of engine part to part variation, component ageing and fuel quality diversity. The extent to which these effects can be counteracted is determined by the detection limits of the virtual combustion sensor. To determine the limitation of the virtual combustion sensor, a virtual combustion sensor system was implemented based on a one-zone heat-release analysis, including the signal processing of the pressure sensor input. The typical error sources in a heavy-duty engine were identified and quantified. The virtual combustion sensor system was presented with flawed signals and the sensor’s sensitivities to the errors were quantified.

The upcoming European legislation for heavy duty vehicles, EuVI, includes rules on monitoring of urea consumption and urea tank volume. These new rules put new demands on the level sensing system monitoring the urea tank. The normal vehicle mounted liquid level sensing system today consists of a single, more or less vertically placed, sensor. When the vehicle is tilted the level of the fluid at the sensor position normally changes. This results in a measurement error in the calculated volume, as the volume is calculated based only on the information from the level sensor. The presented modeling studies investigate the feasibility of using sensor fusion to improve the accuracy of liquid volume estimation on a heavy duty truck. In the first study, the signals from multiple level sensors located in various liquid containing tanks on the truck are fused.

Fast charging of batteries at cold conditions faces the challenge of promoting undesired cell degradation phenomena such as lithium plating. The occurrence of lithium plating is strongly related to local surface potentials and temperatures involving the scales of the electrode surface, the unit cell and the entire module or pack. A multi-scale, multi-domain model is presented, enhancing a Newman based unit cell model with consistent models for heat generation and lithium plating and integrating this 1D+1D approach into a thermal 3D model on module level. The basic equations are presented and three different plating models from literature are discussed. The thermal model is assessed in open-loop simulations and the different plating approaches are compared in charge/discharge simulations at different operating conditions. The full multi-scale, multi-domain model is applied as a virtual sensor for model-based control of fast charging at cold conditions.

This work elaborates the transferability of electrode diffusion coefficients gained from fitting procedures in frequency domain to an electrochemical battery model run in time domain. An electrochemical battery model of an NMC622 half-cell electrode is simulated with sinusoidal current excitations at different frequencies. The current and voltage signals are analyzed in frequency domain via Nyquist and Bode plots. The frequency domain analysis of time domain simulations is applied to assess the numerical convergence of the simulation and the sensitivity on particle diameter, electrode and electrolyte diffusion coefficients. The simulated frequency spectra are used to fit the electrode diffusion coefficient by means of different electrical equivalent circuit models and the electrochemical battery model itself. The fitted diffusion coefficients from the different electrical equivalent circuit models deviate by one order of magnitude from the a priori known reference data.

The combustion in a direct injected internal combustion engine is normally open-loop controlled. The introduction of cylinder pressure sensors enables a virtual combustion sensor which in turn enables closed-loop combustion control, and the possibility to counteract effects such as engine part-to-part variation, component ageing and fuel quality diversity. Closed-loop combustion control requires precise, robust and preferably cheap sensors. This paper presents an investigation of the robustness and the limitation of a knock sensor based virtual combustion sensor. This virtual combustion sensor utilize the common heat release analysis using a knock sensor based virtual cylinder pressure signal. Major virtual sensor error sources in a heavy-duty engine were identified as: the specific heat ratio model, the boost pressure and the crank angle phasing. The virtual sensor errors were quantified in relation to both the measured cylinder pressure and the total virtual sensor error.

Increasing demands for more efficient engines and stricter legislations on exhaust emissions require more accurate control of the engine operating parameters. Engine control is based on sensors monitoring the condition of the engine. Numerous sensors, in a complex control context, increase the complexity, the fragility and the cost of the system. An alternative to physical sensors are virtual sensors, observers used to monitor parameters of the engine thus reducing both the fragility and the production cost but with a slight increase of the complexity. In the current paper a virtual intake manifold cylinder port pressure sensor is presented. The virtual sensor is based on a compressible flow model and on the pressure signal of the intake manifold pressure sensor. It uses the linearized pressure coefficient approach to keep vital performance behaviors while still conserving calibration effort and embedded system memory.

Knowing the tire pressure during driving is essential since it affects multiple tire properties such as rolling resistance, uneven wear, and how prone the tire is to tire bursts. Tire temperature and cavity pressure are closely tied to each other; a change in tire temperature will cause an alteration in tire cavity pressure. This article gives insights into which tire temperature measurement position is representative enough to estimate pressure changes inside the tire, and whether the pressure changes can be assumed to be nearly isochoric. Climate wind tunnel and road measurements were conducted where tire pressure and temperature at the tire inner liner, the tire shoulder, and the tread surface were monitored. The measurements show that tires do not have a uniform temperature distribution. The ideal gas law is used to estimate the tire pressure from the measured temperatures.

Calibrating a vehicle’s powertrain for dynamic operation needs to focus on efforts to mitigate the risks of thermal overload which may arise in the stator or rotor components of an e-motor. Risks also may arise for expected NVH or durability targets, with torque and torque “oscillations” acting as primary sources for the vehicles’ NVH behavior. Both topics, temperature measurement of stator and rotor as well as dynamic torque measurements of the powertrain’s drive shaft are addressed with examples demonstrating the sensors applications in normal test bed and vehicle configurations.

The parameterization of the electrochemical pseudo-two-dimensional (P2D) model plays an important role as it determines the acceptance and application range of subsequent simulation studies. Electrochemical impedance spectroscopy (EIS) is commonly applied to characterize batteries and to obtain the exchange current density and the solid diffusion coefficient of a given electrode material. EIS measurements performed with frequencies ranging from 1 MHz down to 10 mHz typically do not cover clearly isolated solid state diffusion processes of lithium ions in positive or negative electrode materials. To extend the frequency range down to 10 μHz, the distribution function of relaxation times (DRT) is a promising analysis method. It can be applied to time-domain measurements where the battery is excited by a current pulse and relaxed for a certain period.

Typically the combustion in a direct injected compression ignited internal combustion engine is open-loop controlled. The introduction of a cylinder pressure sensor opens up the possibility of a virtual combustion sensor which could enable closed-loop combustion control and thus the potential to counteract effects such as engine part to part variation, component ageing and fuel quality diversity. Closed-loop combustion control requires precise, robust and preferably cheap sensors. This paper presents a virtual cylinder pressure sensor based on the signal from the inexpensive but well proven knock sensor. The method used to convert the knock sensor signal into a pressure estimate included the stages: Phase correcting the raw signal, Filtering the raw signal, Scaling the signal to known thermodynamic laws and provided engine sensors signals and Reconstructing parts of the signal with other known models and assumptions.