Strategies For Automated Validation Of Infotainment For Electric Vehicles

Considering the intra-vehicle communication protocols and the performance while having an increased data load and security threats, the Controller Area Network- Flexible Data rate (CAN FD) protocol is becoming common for crucial functionalities according to its benefits. The industry demands an effort, which puts all the mentioned points together and provides an automated solution to validate the infotainment system to increase efficiency. The scope of the project is to make an internal automated test bench tool able to test the CAN FD network along with the CAN network used in the infotainment system of battery electric vehicles

Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications

We address the problem of diagnosing and repairing specifications for hybrid systems formalized in signal temporal logic (STL). Our focus is on the setting of automatic synthesis of controllers in a model predictive control (MPC) framework. We build on recent approaches that reduce the controller synthesis problem to solving one or more mixed integer linear programs (MILPs), where infeasibility of a MILP usually indicates unrealizability of the controller synthesis problem. Given an infeasible STL synthesis problem, we present algorithms that provide feedback on the reasons for unrealizability, and suggestions for making it realizable. Our algorithms are sound and complete, i.e., they provide a correct diagnosis, and always terminate with a non-trivial specification that is feasible using the chosen synthesis method, when such a solution exists. We demonstrate the effectiveness of our approach on the synthesis of controllers for various cyber-physical systems, including an autonomous driving application and an aircraft electric power system

Vibration isolation with smart fluid dampers: a benchmarking study

The non-linear behaviour of electrorheological (ER) and magnetorheological (MR) dampers makes it difficult to design effective control strategies, and as a consequence a wide range of control systems have been proposed in the literature. These previous studies have not always compared the performance to equivalent passive systems, alternative control designs, or idealised active systems. As a result it is often impossible to compare the performance of different smart damper control strategies. This article provides some insight into the relative performance of two MR damper control strategies: on/off control and feedback linearisation. The performance of both strategies is benchmarked against ideal passive, semi-active and fully active damping. The study relies upon a previously developed model of an MR damper, which in this work is validated experimentally under closed-loop conditions with a broadband mechanical excitation. Two vibration isolation case studies are investigated: a single-degree-of-freedom mass-isolator, and a two-degree-of-freedom system that represents a vehicle suspension system. In both cases, a variety of broadband mechanical excitations are used and the results analysed in the frequency domain. It is shown that although on/off control is more straightforward to implement, its performance is worse than the feedback linearisation strategy, and can be extremely sensitive to the excitation conditions

Adaptive neuro-fuzzy technique for autonomous ground vehicle navigation

This article proposes an adaptive neuro-fuzzy inference system (ANFIS) for solving navigation problems of an autonomous ground vehicle (AGV). The system consists of four ANFIS controllers; two of which are used for regulating both the left and right angular velocities of the AGV in order to reach the target position; and other two ANFIS controllers are used for optimal heading adjustment in order to avoid obstacles. The two velocity controllers receive three sensor inputs: front distance (FD); right distance (RD) and left distance (LD) for the low-level motion control. Two heading controllers deploy the angle difference (AD) between the heading of AGV and the angle to the target to choose the optimal direction. The simulation experiments have been carried out under two different scenarios to investigate the feasibility of the proposed ANFIS technique. The simulation results have been presented using MATLAB software package; showing that ANFIS is capable of performing the navigation and path planning task safely and efficiently in a workspace populated with static obstacles

Sensor fault detection with low computational cost : a proposed neural network-based control scheme

The paper describes a low computational power method for detecting sensor faults. A typical fault detection unit for multiple sensor fault detection with modelbased approaches, requires a bank of estimators. The estimators can be either observer or artificial intelligence based. The proposed control scheme uses an artificial intelligence approach for the development of the fault detection unit abbreviated as ‘i-FD’. In contrast with the bank-estimators approach the proposed i-FD unit is using only one estimator for multiple sensor fault detection. The efficacy of the scheme is tested on an Electro-Magnetic Suspension (EMS) system and compared with a bank of Kalman estimators in simulation environment

Hardware-in-the-loop simulation of magnetorheological dampers for vehicle suspension systems

Magnetorheological (MR) fluids provide an elegant means to enhance vibration control in primary vehicle suspensions. Such fluids can rapidly modify their flow characteristics in response to a magnetic field, so they can be used to create semi-active dampers. However, the behaviour of MR dampers is inherently non-linear and as a consequence, the choice of an effective control strategy remains an unresolved problem. Previous research has developed a method to linearize the damper's force/velocity response, to allow implementation of classical control techniques. In the present study, this strategy is used to implement skyhook damping laws within primary automotive suspensions. To simulate the vehicle suspension, a two-degree-of-freedom quarter car model is used, which is excited by realistic road profiles. The controller performance is investigated experimentally using the hardware-in-the-loop-simulation (HILS) method. This experimental method is described in detail and its performance is validated against numerical simulations for a simplified problem. The present authors demonstrate that feedback linearization can provide significant performance enhancements in terms of passenger comfort, road holding, and suspension working space compared with other control strategies. Furthermore, feedback linearization is shown to desensitize the controller to uncertainties in the input excitation such as changes in severity of the road surface roughness