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The use of electric motors to independently control the torque of two or four wheels of a vehicle has the potential to significantly improve safety and handling. One virtue of electric motors is that their output torque can be accurately estimated. Using this known output torque, longitudinal tire force and coefficient of friction can be estimated via a controller output observer. This observer works by constructing a model of wheel dynamics, with longitudinal tire force as an unknown input quantity. A known wheel torque is input to the physical and modeled system and the resulting measured and predicted wheel speeds are compared. The error between the measured and predicted wheel speed is driven towards zero by a robust feedback controller. This controller modulates an estimate of longitudinal tire force used as an input by the wheel dynamics model. The resulting estimate of longitudinal tire force quickly converges towards the actual value with minimal computational expense.

A new control strategy for wheel slip control, considering the complete dynamics of the electro-hydraulic brake (EHB) system, is developed and experimentally validated in Cranfield University's HiL system. The control system is based on closed loop shaping Youla-parameterization method. The plant model is linearized about the nominal operating point, a Youla parameter is defined for all stabilizing feedback controller and control performance is achieved by employing closed loop shaping technique. The stability and performance of the controller are investigated in frequency and time domain, and verified by experiments using real EHB smart actuator fitted into the HiL system with driver in the loop.

A unique concept for a multi-body test rig enabling the simulation of longitudinal, steering and vertical dynamics was developed at the Institute for Mechatronic Systems (IMS) at TU Darmstadt. A prototype of this IMS test rig is currently being built. In conjunction with the IMS test rig, the Vehicle Terrain Performance Laboratory (VTPL) at Virginia Tech further developed a full car, seven degree of freedom (7 DOF) simulation model capable of accurately reproducing measured displacement, pitch, and roll of the vehicle body due to terrain excitation. The results of the 7 DOF car model were used as the reference input to the multi-body IMS test rig model. The goal of the IMS/VTPL joint effort was to determine whether or not a controller for the IMS test rig vertical actuator could accurately reproduce wheel displacements due to different measured terrain constraints.

Autonomous guided vehicles, called AGVs, are important components of factory automation and manufacture system integration that requires both technical and management skills. In this paper, an AGV prototype equipped with IR detectors and IR range sensors is programming to follow a route line on the floor and avoid some obstacles on the way. The motion of the experimental AGV is promote by two DC motor with build-in gearbox, working with simultaneous PWM control in closed-loop operation. This AGV is designed to operate in environments such as offices and shop floor, in order to carry light loads on flat surfaces and ramps with positive and negative inclination. Simulations tests with ADAMS® are compared with some experimental results in order to validate the model and the prototype approaches.

Referring to the transmission development, three different classifications of the power train are useful. These are the conventional power train with combustion-engined drive of the wheels, the electric power train with electromotive drive of the wheels and the hybrid power train with both types of drive. Due to this division, the micro hybrid belongs to the conventional power train while the serial hybrid is classified with the electric power train. Subdivisions of the electric power train are the decentralized drives near the axle shafts or the wheel hub drive and the central drive with differential. The choice of the electric motor is dependent on different influences such as the package, the costs or the application area. Furthermore the execution of the transmission system does influence the electric motor. Wheel hub drives are usually executed on wheel speed level or with single ratio transmission.

The “Two-Drive-Transmission with Range-Extender” (called DE-REX) is an innovative hybrid powertrain concept using two electric motors and an internal combustion engine. The two electric motors are permanent magnet synchronous motors with a maximum power of 48 kW each. As combustion engine a 3 cylinder, turbocharged engine with a power of 65 kW is used. The aggregates are coupled to a transmission whose layout is characterized by consisting of two parallel 2-speed sub-transmissions. This layout offers a high flexibility and enables both parallel and series hybrid driving. The hybrid control unit (HCU) has to select the optimal driving mode and power distribution between the aggregates in regard to in some extend competing objectives like efficiency, emissions or driving comfort. In particular, the operation of the internal combustion engine with only two gear ratios is challenging.

Developing an energy-efficient powertrain system is a solution for environment-friendly vehicles. Furthermore, it also enhances the performance of vehicles. In powertrain system, transmission plays an important role in terms of vehicle dynamic performance and energy consumption. Therefore, a lot of researches have been conducted on modelling power losses inside the transmission. Basically, the power losses in transmission consist of bearing losses, drag torque losses on gear blank that is immersed in the oil and gear mesh losses due to the sliding frictional force on gear flank. According to some experiments in the latest literatures, power losses of synchronizers cannot be neglected, when its shift sleeve is in neutral position. Principally, power losses of synchronizers in neutral position mainly come from load independent drag torque.

The underlying basic model represents a powertrain with automatic transmission including a torque converter. It is based on a greybox-modeling approach, which refers to ordinary differential equations with identified parameters and characteristic curves. The validated basic model is extended in order to reproduce the system behavior and especially the side shaft torque during a gear shift process. Therefore the model is extended by a transmission model with clutches for gear shifting in order to simulate specific powertrain dynamics additionally. The parameters have already been determined for the basic model using a method for isolated and structured parameter identification based on measurement data of an automotive powertrain test bench. A comparable structured parameter identification method is applied to obtain the parameters of the extended model.

Besides optimal engine systems, high-efficiency vehicle transmissions are generally also required to improve fuel economy in automotive applications. For the energy loss analysis in transmissions, most research focused on the major mechanical components, such as gears, bearings and seals, while the other mechanical losses, like synchronizer losses, were usually not considered. With increasing number of synchronizers in modern transmissions, a recent study indicates that the power loss analysis of synchronizers should also be developed and appended for a more accurate investigation on overall power losses in transmissions. The function of synchronizer is to equalize the different rotational speeds of shafts and gear wheels by frictional torques, for which the synchronizer must be cooled and lubricated in order to enhance the service life. With the supplement of lubricants, fluid friction is generated due to the differential speed, when the synchronizer is in neutral position.

In the evolving landscape of automated driving systems, the critical role of vehicle localization within the autonomous driving stack is increasingly evident. Traditional reliance on Global Navigation Satellite Systems (GNSS) proves to be inadequate, especially in urban areas where signal obstruction and multipath effects degrade accuracy. Addressing this challenge, this paper details the enhancement of a localization system for autonomous public transport vehicles, focusing on mitigating GNSS errors through the integration of a LiDAR sensor. The approach involves creating a 3D map using the factor graph-based LIO-SAM algorithm based on GNSS, vehicle odometry, IMU and LiDAR data. The algorithm is adapted to the use-case by adding a velocity factor and altitude data from a Digital Terrain model. Based on the map a state estimator is proposed, which combines high-frequency LiDAR odometry based on FAST-LIO with low-frequency absolute multiscale ICP-based LiDAR position estimation.