McLaren Honda (United Kingdom)

In passenger cars, the ride characteristics are fundamental to the driver and passenger engagement, as they define the comfort and road holding performance. Therefore, the methods and tools to assess ride quality are of significant interest to the vehicle dynamics specialists, and are an important part of the internal know-how of each car maker and Tier 1 supplier, which is often kept confidential. Unfortunately, the available literature does not include a comprehensive survey on the evaluation of the objective and subjective aspects related to ride, and their correlation. This review targets the gap, and deals with: (i) the available tools and techniques to objectively assess primary and secondary ride, including typical manoeuvres, road profiles, required vehicle instrumentation, and key performance indicators (KPIs); (ii) the subjective attributes and their categorisation; (iii) the approaches and mathematical models to correlate the objective KPIs with the subjective evaluation; and (iv) future trends. The know-how of the authors on the ride assessment of high-performance passenger cars will also be used to cover the aspects that are currently overlooked by the available literature and standards. In summary, the manuscript provides the interested reader with useful guidance on the procedures to perform ride quality analyses.

In a System Engineering perspective, asset management (AM) is related to a subset of techniques focusing on the in-service phase, aligned with product life-cycle management discipline. Today, within AM solution market, the integration of Artificial Intelligence (AI) technics above traditional entreprise solution is a key trend. This paper is focusing on how symbolic AI and data driven AI could improve some issues of the AM life cycle, in particular in asset acquisition, performance analysis and forecasting, asset monitoring, predictive and prescriptive maintenance, supply chain optimisation including spare parts management…

BackgroundObjective symptom monitoring of patients with Amyotrophic Lateral Sclerosis (ALS) has the potential to provide an important source of information to evaluate the impact of the disease on aspects of real-world functional capacity and activities of daily living in the home setting, providing useful objective outcome measures for clinical trials.ObjectiveThis study aimed to investigate the feasibility of a novel digital platform for remote data collection of multiple symptoms—physical activity, heart rate variability (HRV), and digital speech characteristics—in 25 patients with ALS in an observational clinical trial setting to explore the impact of the devices on patients’ everyday life and to record tolerability related to the devices and study procedures over 48 weeks.MethodsIn this exploratory, noncontrolled, nondrug study, patients attended a clinical site visit every 3 months to perform activity reference tasks while wearing a sensor, to conduct digital speech tests and for conventional ALS monitoring. In addition, patients wore the sensor in their daily life for approximately 3 days every month for the duration of the study.ResultsThe amount and quality of digital speech data captured at the clinical sites were as intended, and there were no significant issues. All the home monitoring sensor data available were propagated through the system and were received as expected. However, the amount and quality of physical activity home monitoring data were lower than anticipated. A total of 3 or more days (or partial days) of data were recorded for 65% of protocol time points, with no data collected for 24% of time points. At baseline, 24 of 25 patients provided data, reduced to 13 of 18 patients at Week 48. Lower-than-expected quality HRV data were obtained, likely because of poor contact between the sensor and the skin. In total, 6 of 25 patients had mild or moderate adverse events (AEs) in the skin and subcutaneous tissue disorders category because of skin irritation caused by the electrode patch. There were no reports of serious AEs or deaths. Most patients found the sensor comfortable, with no or minimal impact on daily activities.ConclusionsThe platform can measure physical activity in patients with ALS in their home environment; patients used the equipment successfully, and it was generally well tolerated. The quantity of home monitoring physical activity data was lower than expected, although it was sufficient to allow investigation of novel physical activity end points. Good-quality in-clinic speech data were successfully captured for analysis. Future studies using objective patient monitoring approaches, combined with the most current technological advances, may be useful to elucidate novel digital biomarkers of disease progression.

Despite recent advances in MEMS vibration energy harvesting and ultra-low power wireless sensors, designing a wireless sensor system entirely powered by a single MEMS device under noisy base excitation has remained a challenge. This paper presents a wireless sensor system co-integrated with a single MEMS piezoelectric vibration energy harvester chip excited by band-limited large amplitude noisy vibration characteristic of an automotive application. The use of soft stoppers in the MEMS package enables the harvesters to operate at an excitation level of 10 g(rms). A custom thick AlN (Aluminum Nitride) piezoelectric process is employed to fabricate the MEMS harvesters with a single MEMS chip generating 179 μW rectified power under these excitation conditions. A low-power wireless sensor module and a receiver module were also designed and demonstrated in this work. Experiments show that the wireless sensor module can be powered solely by the MEMS energy harvester commencing from the cold state. Successful wireless data transmission and receival of sensor data packets are recorded under representative conditions.

We investigated the association of pre-operative activity, reported by the Duke Activity Score Index, Short Form-12 and measured by an accelerometer worn at home, with five cardiopulmonary exercise variables: peak power; peak oxygen consumption; anaerobic threshold; and ventilatory equivalents for oxygen and carbon dioxide. Fifty patients scheduled for major surgery underwent a standard pre-operative cardiopulmonary exercise test and wore a chest-mounted triaxial accelerometer for a mean (SD) duration of 3.2 (0.4)days. The Duke Activity Score Index and six accelerometer variables were significantly correlated with all five cardiopulmonary exercise variables, Pearson correlation coefficients 0.5-0.7, p=0.02 to p<0.001. Our results can guide future studies that measure physical activity for pre-operative assessment and interventions.

Roll motion in ships is a major cause for problems to passengers and human operators. The reduction of vessel roll, or roll damping, has been widely addressed in the control literature as surveyed in Perez, Ship motion control: course keeping and roll stabilization using rudder and fins (2005). The considered set-up is shown in Fig. 8.1. The system, controlled by rudder and fins, is fully-actuated.

This paper addresses the problem of optimal control for semi-active vehicle suspensions. A specific goal is to develop an algorithm which is capable of optimising ride and handling behaviour simultaneously in an experimental situation. A time-domain optimal control approach is adopted in which ride and handling are modelled as exogenous disturbances acting on the vehicle: road disturbances (modelled stochastically), and driver inputs (treated as deterministic quasi-static disturbances). A control algorithm is derived from a solution of the stochastic Hamilton–Jacobi–Bellman equation for the finite horizon case. The advantages of the approach are demonstrated experimentally on a test vehicle performing a steering manoeuvre on a bumpy roundabout.