«The optimal performance of groups of elevators is a complex mathematical problem because the characteristics of groups, their transport capacities and time-dependent service qualities and the traffic density patterns generated by populations served, are interdependent with each other. This problem of long standing has been resolved. The solution is remarkably simple.»

Introduction 2019

Groups with intelligent destination controls feature optimal configurations i.e. optimal numbers of relatively small cars, to meet the requirements of a specific building or zone and its population. Intelligent groups enable optimal group performance for all traffic conditions with contractually guaranteed transport capacities and time-dependent service qualities.

Intelligent groups control numbers of permitted stops i.e. the dimension time, to assure optimal performance. The mathematical models of workbooks RSimxx facilitate group performance calculations (“stress tests”) for any combination of up and down traffic densities. These calculations prove and demonstrate that the dimension time is decisive for group performance and group characteristics. The basis of the mathematical model are the door-to-door flight times (DDFT’s) of cars for any travel distance and contract speed. DDFT’s define the “muscle” power of elevators; they represent the contribution of elevator technology to group performance.

Stress tests use identical carloads i.e. identical numbers of passengers, which define traffic densities in the same way as carloads define the traffic densities of installed groups.These conditions facilitate comparison of transport capacities and time-dependent service qualities of groups with different configurations.  The comparisons reveal how and why group configurations affect group performance data, and the paramount importance of the number of cars. These insights facilitate selection of group configurations, which meet the specific requirements of building owners and architects for a specific building. For detailed explanations, please refer to chapter F.

The original objective of the book "The planning and performance of groups of elevators" in 2006, was to induce the elevator industry to engage in the research of optimal group performance after the discovery of the inherent relativity of group characteristics. Regrettably, elevator companies could not be motivated for this research. Subsequently this topic became a personal research project of the author. This book is now a “work in progress” to inform about the potential of intelligent group controls and optimal performance.

An important aspect of intelligent group controls is the optimal positioning of cars in “the rotating string of cars” that defines each group as a vertical transportation system. Intelligent groups know the exact position of each car, the numbers and destinations of their passengers, the distances between cars, etc. A call for transport may enable an approaching car to stop and provide a waiting passenger with a very short waiting time. However, this may not be an optimal decision. If the distance to the next following car is short, the first possible car will probably not stop and increase its distance to the following car. To cut a long story short: Intelligent groups will avoid very short waiting times and “bunching” of cars.

Avoidance of short waiting times implies that a further passenger may join a waiting person. Consequently opportunities to collect more passengers per stop and for more passengers having the same destinations, increase. Groups with many small cars may idle one or more cars during medium traffic conditions, to reduce energy consumption. Idle cars are available for special services. All control decisions of intelligent groups are logical, consequently intelligent group controls will be the most simple group control system.

Exact group planning and intelligent destination controls end a century of insecurity in respect of group planning and performance.