Car Control Unit Research Articles

Charging balance management technology for low-voltage battery in the car control unit with combined power system

The article presents the results of mathematical models and algorithms development complex, which is aimed at ensuring a positive charge balance of an automobile low-voltage rechargeable battery in car control systems with a hybrid power system. The aim of the work is to create and implement a set of software and mathematical models on one of the existing passenger car model, using the default components and systems of the car, to achieve a positive energy balance of the automotive low-voltage power network, and also to solve the problem of battery discharge by normalizing the turn-on time of powerful consumers leading to fast battery discharge. As criteria for the optimal performance of the proposed models and algorithms, the SOC parameters are considered - state of charge (%), battery charge (A * h), charge and discharge current of a battery (A), voltage on a battery during its charge when a charging current is absent or in a quiescent state (V), ambient temperature (˚C). Authors defined: composition of a control system, the necessary logic and a set of mathematical models implemented by electronic systems to control the charging balance of the automotive low-voltage power supply network, connections and functions of systems and components. As a result of a full-scale experiment, charge and discharge graphs, experimental data, current characteristics and dynamics of their changes during operation, experimental time-current dependencies during the operation of each component of a low-voltage power grid were obtained. The results of the work support to improve energy balance of an electrical power network, increase the efficiency and service life cycle of batteries, formulate system and technical requirements for control systems and their subsequent implementation. Versatility solutions are provided for improving management of charge balance car battery.

Designing Navigation and Obstacle Avoidance System Combining Smart Car And Quadrotor Aircraft

The navigation and obstacle avoidance system combining smart car and quadrotor aircraft takes MK60FX512VLQ15 microcontroller as the intelligent car control unit and STM32F767IGT as the image processing unit of flying platform. This system first collects image information through the infrared camera equipped in the quadrotor aircraft, and sends it to the processing unit for extraction and processing. Then this system transmits the information to the smart car master through the NRF2.4G wireless module and integrates it with the smart car’s own gyroscope data. In this way, the system is able to tell the relative angle of the smart car with the target according to the result, obtain the operating environment and state of the car body through its own ultrasonic ranging, encoder and other modules, and adjust the car’s speed and direction so as to avoid obstacles. The system is smooth in operation, flexible in adjusting speed and direction, and is fully capable of avoiding obstacles.

Guidelines for the design of tyre sensor housings

The next generation of tyre sensors will be bonded directly onto the inner liner (IL) in order to measure important parameters such as strain, vehicle load, contact pressure, the tyre-road friction coefficient or wear. Sensor packages (SP) have a sensor node, which is bonded and kept in position by a specifically designed rubber housing (RH). Since the measurements they provide to the car control unit are used to improve the active or passive safety of vehicles, these packages can be considered critical safety components that should be dimensioned carefully. A tyre analysis, whether statical or dynamical, in which the complete structure is considered, under any load, inflating pressure or temperature working condition is mainly oriented towards defining the tyre product. The insertion of an SP inside such a complex tyre model, with the purpose of only analysing its behaviour, would be too time consuming considering the strong nonlinear behaviour of the tyre model. Therefore, this work presents a method that can be used to define a computationally lightweight finite element method (FEM) simulation, which is able to recreate the working conditions to which an SP is subjected. The basic idea behind this method is to separate the analysis of the SP from the structural tyre analyses; the latter is only run once, independently. The first task is to impose the deformed shape on a simplified model of the tyre with a bonded SP. All the deformation states that occur during rolling are computed in a static FEM simulation. The second task is to apply the inertial forces that act on the SP, whether computed or measured directly on the tyre, as external loads. These tasks are implemented in user-defined routines that are executed by the FEM solver. The method permits the stress concentration inside the RH material volume to be identified, at any angular position of the wheel. This information is then used, during the design process, to identify the most suitable geometry to level out the stress distribution. The resulting shape can be tested under different boundary conditions, by substituting the corresponding data arrays, but using the same FEM model. Since the deformed shapes and inertial forces are stored as simple text matrices (which are also used to form a test library), they can be easily interchanged in a flexible way. This more extended design process can reduce the costs of prototyping moulds. The proposed methodology has been developed and tested for the Pirelli Cyber TM Tyre project.

A train air brake force model: Car control unit and numerical results

This and a companion paper focus on the integration of a model of a train’s air brake and a non-linear model of a train’s dynamics based on the use of trajectory coordinate formulations. The forces developed by the air brake depend on various system components, including the automatic brake valve, the brake pipe and the car control unit (CCU). The developed braking forces, which depend on the position of handle of the automatic brake valve, are applied to the wheels using the CCU located along the brake pipe and enter into the formulation of the non-linear dynamic equations for the train in addition to other external forces. In order to develop an efficient computational procedure, simplified valve models, with more straightforward operation modes, are considered in order to reduce the computational overhead. The CCU used in this research has a control valve connected to three main pneumatic components: the auxiliary reservoir, the emergency reservoir and the brake cylinder. The reservoirs are the main storage area of the pressurized air, while the brake cylinder transmits the brake force to the wheels using the mechanical components of the CCU, including the brake rigging and the brake shoes. The communications between different parts connected to the control valve are controlled by its slide valve that can be positioned in the brake application, brake release and lap positions. It is also assumed that the CCU modeled in this study has the emergency portion that enables it to apply emergency braking, including the effect of the CCU’s emergency vent valve. In this paper, a mathematical model for the CCU is developed, while the locomotive automatic brake valve and brake pipe models are developed in a companion paper. The relationship between the main components of the air brake system and the train dynamics is discussed, and the final set of differential equations that includes the two models is presented. Furthermore, different computer simulation scenarios are considered in this paper in order to investigate the effect of the air brake forces on the train’s longitudinal dynamics for cases of different braking modes. The numerical results, obtained in this study, are compared with experimental results published in the literature.

A train air brake force model: Locomotive automatic brake valve and brake pipe flow formulations

The goal of this study is to integrate an air brake model with efficient algorithms for train longitudinal force calculation that are based on trajectory coordinate formulations. The air brake model, developed in this investigation and presented in this paper and a companion paper, consists of the locomotive automatic brake valve, air brake pipe and car control unit (CCU). The proposed air brake force model accounts for the effect of the air flow in long train pipes as well as the effect of leakage and branch pipe flows. This model can be used to study the dynamic behavior of the air flow in the train pipe and its effect on the longitudinal train forces during brake application and release. The governing equations of the air pressure flow are developed using the general fluid continuity and momentum equations, simplified using the assumptions of one-dimensional isothermal flow. Using these assumptions, one obtains two coupled air velocity/pressure partial differential equations that depend on time and the longitudinal coordinate of the brake pipes. The partial differential equations are converted to a set of first-order ordinary differential equations using the finite element method. The resulting air brake ordinary differential equations are solved simultaneously with the train’s second-order non-linear dynamic differential equations of motion that are based on the trajectory coordinates. The train car non-linear dynamics is defined using a body track coordinate system that follows the car motion. The body track coordinate system translation and orientation are defined in terms of one parameter that describes the distance traveled by the car. The configuration of the car with respect to its track coordinate system is described using two translation coordinates and three Euler angles. The operation modes of the brake system considered in this investigation are the brake release mode and the brake application mode that includes service and emergency brakes. A detailed model of the locomotive automatic brake valve is presented in this investigation and used to define the inputs to the air brake pipe during the simulation. A simplified model of this valve is also proposed in order to reduce the computational time of the simulation. In a companion paper, the detailed CCU formulation is presented. The coupling between the air brake, locomotive automatic brake valve, CCUs and train equations is established and used in the companion paper in the simulation of the non-linear dynamics of long trains. The air brake formulations presented in the two companion papers are implemented in a computer code called Analysis of Train/Track Interaction Forces (ATTIF) which is developed for the analysis of longitudinal train forces.

Design of Monitoring System on Pulley Car

A type of design method of monitoring system on pulley car is introduced. The system is composed of car control unit, ground control unit, communication unit and computer management unit. The key element of system is based on induction radio communication technology. The position of pulley car can be detected dynamically by following hardware and software unit. At the same time, the signal of position is sent to host linked. By watching animation of pulley car, workers standing in workroom can know the position of pulley car accurately at any moment.

Modelling of an automotive dual mass flywheel

Accurate knowledge of the instantaneous friction torque of an automotive clutch is a key claim while achieving comfortable, automated gearshifts, improving fuel economy or reducing wear. Nevertheless, torque sensors are not commonly used in automotive drive trains because of their additional size and costs. Thus, to estimate the clutch torque, a detailed dynamic model of each component integrated into a clutch system is needed.In the following, a nonlinear dynamic model of a Dual Mass Flywheel (DMF) as autonomous part of a clutch system is presented and verified by test bench data. A DMF is used to reduce the cyclic irregularity of the torque generated by a combustion engine. It is typically assembled between crankshaft and clutch. The level of detail of the modelled DMF dynamics is chosen in a way that a real-time simulation on a car's control unit is feasible. Using the engine speed and the clutch torque as model inputs, the proposed model has the ability to simulate the DMF deflection and therefore the clutch rotational speed. Resulting torques acting on the DMF's primary and secondary mass are reconstructed, too. If both rotation speeds of the DMF masses (the engine and clutch speed) can be measured, this model can also be used to reconstruct the clutch torque.